THE ANALYSIS OF TRANSLATION TECHNIQUES AND …/The... · (Albert Einstein) vi DEDICATION This...

THE ANALYSIS OF TRANSLATION TECHNIQUES AND QUALITY OF TRANSLATION

OF THE WEBSITE “FRIENDSTER.COM”

THESIS

Submitted as a Partial Fulfilment of the Requirements for Sarjana Sastra Degree at English Department

By:

LAMBANG PRAKOSO

C 0305040

ENGLISH DEPARTMENT FACULTY OF LETTERS AND FINE ARTS

SEBELAS MARET UNIVERSITY SURAKARTA

2010

ii

THESIS APPROVAL THE ANALYSIS OF TRANSLATION TECHNIQUES

AND QUALITY OF TRANSLATION OF THE WEBSITE “FRIENDSTER.COM”

Written By:

Lambang Prakoso

C 0305040

Approved to be examined before the Board of Examiners Faculty of Letters and Fine Arts

Sebelas Maret University

Thesis Consultant:

Ida Kusumadewi, SS, MA

NIP. 19710525 199802 2 001

Head of English Department

Dr. Djatmika, MA

NIP. 19670726 199302 1 001

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THE ANALYSIS OF TRANSLATION TERCHNIQUES AND QUALITY OF TRANSLATION

OF THE WEBSITE “FRIENDSTER.COM”

Written By: Lambang Prakoso

C 0305040

Accepted and Approved by the Board of Examiners Faculty of Letters and Fine Arts

Sebelas Maret University On

Position Name Signature Chairman Dr. Djatmika, MA (…………………) NIP. 19670726 199302 1 001 Secretary Drs. Agus Hari Wibowo, MA (………………....) NIP. 19670830 199302 1 001 First Examiner Ida Kusuma Dewi, SS, MA (…………………) NIP. 19710525 199802 2 001 Second Examiner Dr. Tri Wiratno, MA (………………. ..) NIP. 19610914 198703 1 001

The Dean of Faculty of Letters and Fine Arts Sebelas Maret University

Drs. Sudarno, MA NIP. 19530314 198506 1 001

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PRONOUNCEMENT

Name : Lambang Prakoso

NIM : C 0305040

Stated wholeheartedly that the thesis entitled “The Analysis of

Translation Techniques and Quality of Translation of the Website

Friendster.com” is originally made by the researcher. It is not plagiarism, nor

made by the others. The things related to other people’s work are written in

quotation and included within the bibliography.

If it is then proved that the researcher cheats, the researcher is ready to

take the responsibility.

Surakarta, Februari 2010

The researcher,

Lambang Prakoso

v

MOTTO

v “Surely with difficulty is ease. With difficulty is

surely eased.” (QS: Alam Nasyrah : 5-6)

v You can if you think you can. (George Reeves)

v Imagination is more important than knowledge.

(Albert Einstein)

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DEDICATION

This thesis is dedicated to:

Allah SWT, the Lord of the Universe

The Prophet Mohammed, Peace be Upon Him

My beloved Ibu and Bapak

My Little Brother

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ACKNOWLEDGMENT

Bismillahirrohmannirrohim

Alhamdulillah, I want to thank, Allah SWT, for everything given to me.

With all blessing, love, and guidance given to me, I can finish this thesis as a

partial fulfilment of graduating requirement of the Sarjana Degree.

In finishing this thesis, I got supports and helps from people around me.

Therefore, I want to give my deepest gratitude to all the people who have given

important contributions. It goes to:

1. The Dean of the Faculty of Letters and Fine Arts, for approving this thesis.

2. The Head of the English Department, Dr. Djatmika, MA, for his

permission to conduct this thesis.

3. My thesis advisor, Ida Kusuma Dewi, SS, MA, for her advices and

assistance. Thank you very much.

4. Drs. Hari Wibowo, MA and Dr. Tri Wiratno, for being my thesis

examiners.

5. My academic consultant, Taufik Al Makmun, SS, for his assistance during

my study.

6. All the lecturers who have taught and gave me precious knowledge. Thank

you very much for many unforgettable classes we had.

7. The three raters, Mr. Heri Nababan, Mr. Sumardiono, and Mr. Alif for the

valuable contributions in this thesis.

8. The 18 respondents from XII TKJ SMK Negeri 1 Boyolali for being my

respondents.

9. My beloved Ibu (Tutut Daryani) and Bapak (Sukadi) for the big love and

cares. Thank you for your supports and prays. You are wonderful parents

ever. My little brother, Ruruh Kayadi.

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10. Pakdhe Noto. Thank you for your helps and your suggestions. You are

like my second father. Thank you for your inspiring words: “dadi wong ki

sing sabar, kabeh kuwi anggepen prihatin.”, “ora usah meri, rejekine

uwong ki bedo-bedo, bejone uwong ki bedo-bedo.”, and also “pikiran

orang bisa berubah tak hanya dalam hitungan bulan, minggu, hari,

ataupun jam, hanya dalam 1 detik pun pikiran orang bisa berubah.” I will

always remember that.

11. My beloved friends in ED 2005. “Semangat”, who I can not mention one

by one. Thanks for our togetherness guys. It is so nice to have friends like

you all.

12. Mas Edy Triyanto, Mas Edy M Fata, and Mas Najib. Thank you for being

the best brothers. Thanks for your helps. I really appreciate your advices

and your suggestions in making my thesis.

13. My friends in futsal team, Andika, Adwin, Febri, Alwi, si Bo, Tori, Rudy,

Ucup, Danang, etc. Thanks for all of your jokes guys.

14. Mbak Cindy and Mbak Hilda. I think we should make a ‘Trio’.

15. The Pokeran’s Tim, Himawan ‘Pakdhe’, Giwang, Daniel, Jusmar, Makna,

Mbak Pipit, Kang Ipul, etc. Thanks for the happiness guys.

I realize that this thesis is far from being perfect. Any supporting

criticisms and suggestions are welcomed.

Lambang Prakoso

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TABLE OF CONTENTS

Approval by Thesis Consultant ii

Approval by Board of Examiners iii

Pronouncement iv

Motto v

Dedication vi

Acknowledgment vii

Table of Contents ix

List of Tables xii

Abstract xiii

CHAPTER I : INTRODUCTION

A. Research Background 1

B. Research Limitation 5

C. Problem Statement 5

D. Research Benefits 5

E. Thesis Organization 6

CHAPTER II : LITERATURE REVIEW

A. Definition of Translation 7

B. Types of Translation 8

C. Equivalence 13

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D. Translation Techniques 15

E. Translation Quality Assessment 22

F. Friendster 25

G. Website Localization 26

CHAPTER III: RESEARCH METHODOLOGY

A. Type of Research 29

B. Data Source 29

C. Sample and Sampling Technique 30

D. Method of Data Collection 31

E. Technique Data Analysis 33

F. Research Procedure 34

CHAPTER IV: ANALYSIS

A. Introduction 35

B. Analysis

1. Translation Techniques 35

2. Accuracy 47

3. Acceptability 53

4. Readability 59

C. Discussion 66

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CHAPTER V : CONCLUSION AND RECOMMENDATION

A. Conclusion 76

B. Recommendation 77

BIBLIOGRAPHY

APPENDICES

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LIST OF TABLES

Table 4.1.1 : Addition Technique 37

Table 4.1.2 : Borrowing or Borrowing plus Explanation 38

Table 4.1.3 : Naturalization 39

Table 4.1.4 : Literal Translation 40

Table 4.1.5 : Free Translation 41

Table 4.1.6 : Translation Shifts 45

Table 4.1.7 : Translation Techniques 46

Table 4.2.1 : Accuracy 49

Table 4.2.2 : Acceptability 55

Table 4.2.3 : Readability 60

Table 4.2.4 : Translation techniques and TQA 67

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ABSTRACT

Lambang Prakoso. C0305040. The Analysis of Translation Techniques and Quality of Translation of the Website Friendster.com. Undergraduate Thesis: Surakarta. English Departments, Faculty of Letters and Fine Arts. Sebelas Maret University. 2010. This research belongs to a mixed research of qualitative and quantitative methodology employing descriptive method. It is aimed to describe the translation techniques occurred in the translation and the quality assessment of the translation from the website friendster.com. It is also aimed to find out the quality assessment that covers accuracy, acceptability and readability of the phrases of website friendster.com. This research applies purposive sampling as the sampling technique, since the samples are chosen and determined by the researcher. This research is conducted based on primary and secondary data. The primary data consists of 172 phrases taken from the friendster.com and its translation. The secondary data are taken by distributing questionnaires to some raters and respondents.

The analysis shows that the translation techniques used by the translator in translating the friendster.com are translation shifts, literal translation, naturalization, borrowing or borrowing plus explanation, addition, and free translation.

The analysis on translation accuracy shows that there are 146 data considered to be accurate translation. There 26 data considered to be less accurate with classification It means that, in general, the translation is accurate. The analysis on translation acceptability shows that there are 157 data considered to be acceptable translation. There are 15 data considered to be less acceptable. The analysis on translation readability shows that there are 5 data considered to be readable translation with classification A. There are 101 data considered to be less readable with classification B. There are 66 data considered to be unreadable translation with classification C. It means that, in general, the translation is less readable.

It is hoped that this thesis will be beneficial for the English Department students, especially who study translation, as one of the additional source to enlarge and sharpen knowledge about translation, especially related with website translation. Moreover, they can use this research as a reference to conduct a further research related to this study. The researcher also hopes that this thesis can also stimulate other researchers to conduct a further study related to website translation. This research is also recommended to the translator and designer of friendster.com to improve the quality of the website.

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CHAPTER I

INTRODUCTION

A. Research Background

The use of English as the international language is increasing, in line with

the development of science, technology and literature. This phenomenon is proven

by the large numbers of websites that are growing rapidly recently. In the

globalization era, many people use websites as their part of life. There are many

websites made for different purposes and used by many people in different

countries, and most of websites are written in English. The fact that not all people

in the world speak and understand English as their daily language might raise

problems concerning the way in using websites. In this case, the role of translation

is strongly needed in mediating the publishers of the websites and the users who

do not master English well.

There is a fact that translating websites is different from translating books.

In translating a book, the translator has an opportunity to give some additional

information of the translation because there is no limitation of space, except if

there is limitation from the publisher of the book. In translating websites, on the

contrary, the translator can not be free to give any additional information of the

translation as he or she wants because of the limited space. The structure of the

translation website should be the same as the structure of the original web which

has a fixed template.

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Each website uses different template which has been modified by the

creator. In some parts of websites the texts are written in the box. The translators

can not put any additional information if the texts are written on the box because

of the limited space caused by the box shape. That makes translator unable to

accommodate more texts on it. Meanwhile, for the texts that are written outside of

the box, the translator can put any additional information, even though it can not

be done as freely as translating books due to the limited space of the template of

the website.

Friendster is an online social network website. It has the form like usual

websites that has template containing texts that are written inside and outside of

boxes. Friendster has a language link that can change the displayed text into

Indonesian for the users in Indonesia. It means that there should be translations

from English into Indonesian. However, in the first look of the translation, the

researcher found that some of the translations sound unnatural as Indonesian

expressions. For example, the phrase “dating men” is translated into “pria

berkencan”, and “relationship with men” is translated into “hubungan dengan

pria”. Those translations are accurate. The level of acceptability of the

translations, however, is low.

The following are examples taken from friendster which show the

limitation of space caused by the box shape:

View Messages Create Blog

Edit Friends Edit Comments

Customize Page Edit Profile

Edit Photos

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The above source text is translated as follows:

Lihat Pesan Buat Blog

Edit Teman Edit Komentar

Ubah Halaman Edit Profil

Edit Foto

The following example shows another text of friendster that is not written

in a box:

Source text : Current courses

Translated into: Kelas yang diikuti saat ini.

The above example shows that, the source text is “current courses”, and

then the translator translates it into “Kelas yang diikuti saat ini”. This shows that

the translator has to put additional information to give more understanding

information according to the source text, because the text is not written in the box.

The translator adds “yang diikuti” which makes the translation easier to

understand rather than if it is translated into “kelas saat ini”.

It shows that in translating website, a translator needs to consider not only

the accuracy, the readability, and the acceptability of the translations, but also the

limited space of the website.

The above discussion shows that website translation is something

interesting to investigate. It leads the researcher to analyze the Indonesian

translation of friendster.com.

Friendster is an online social networking service. It is the first online

social network and was founded in California by Jonathan Abrams in the year of

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2002. It is growing very rapidly in recent times and widely used in Asia.

Friendster has over 50 million users worldwide. Friendster is available in many

different languages. It was originally published in English, and then the publisher

created a language link that can change the text displayed on the site to Chinese,

Japanese, Korean, Thailand, Indonesian, or Spanish for other users that do not

understand English well. (www.webupon.com/Social-Networks/The-History-of-

Friendster.102 940)

Friendster had been introduced in Indonesia in 2004 and started to be

popular since the website could be accessed in mobile mode since 2006. Even

thought there are other new popular online social networks websites in Indonesia,

friendster still becomes a part of Indonesian lifestyle. According to small project

that the researcher had done in some internet booths, 3 of 5 people that use

internet are still accessing friendster, even though they had another account for

some other online social networks.

Unlike other online social network websites, friendster is relatively easy to

be operated because it uses simple template of website that eases the users in

accessing it. The users also can change the profile background picture or colour

and choose some interesting background by searching from the special website

that the friendster had prepared by forum of friendster. The users can modify the

profile background picture based on the picture that they want by uploading the

picture to certain websites that have relation with the background maker of

friendster.

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B. Research Limitation

The research limitation is needed to keep our research always focus to the

problem statement. The focus of the analysis is only on the phrases (the unit of

translation analyzed) of the website friendster.com. This research is focused on

analyzing the translation techniques that are used by the translator in translating

the phrases of friendster.com and the quality of the translations in terms of

accuracy, acceptability, and readability.

C. Problem Statements

In this research, the researcher proposes the following problems:

1. What translation techniques are used by the translator in translating phrases of

the website friendster.com?

2. How do the techniques influence the quality of translation in terms of

accuracy, acceptability, and readability of the web friendster.com?

D. Research Benefits

The researcher expects that this research will be useful for:

1. The publisher,

The publisher of friendster.com can make improvement in their translation.

2. English department student,

The research expects that this research can be an additional input in the study

of translation.

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3. Other researchers,

The research expects that this research can be an additional input as a

reference in conducting similar researches.

E. Thesis Organization

The present thesis is organized as follows:

Chapter I: Introduction, containing: research background, research limitation

problem statements, research objectives, research benefits, and thesis

organization.

Chapter II: Literature Review, containing: definition of translation, types of

translation, accuracy, acceptability, readability in translation, translation

strategy, and about friendster.

Chapter III: Research Methodology, consisting: type of research, data source,

sample and sampling technique, method of data collection, technique data

analysis, and research procedure.

Chapter IV: Data Analysis, consisting: introduction, translation techniques

analysis, accuracy analysis, acceptability analysis, and readability analysis,

discussion.

Chapter V: Conclusions and Recommendations.

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CHAPTER II

LITERATURE REVIEW

A. Definition of Translation

Experts propose different definitions of translation. The most famous are

Nida and Taber, Larson, Peter Newmark and Roger T. Bell. Nida and Taber in

their book entitled The Theory and Practice of Translation, the definition of

translation as follows “Translating consist of reproducing the receptor language

the closest natural equivalence of the source language, first in terms of meaning

and secondly in terms of style” (1974:14).

Peter Newmark defines translation as “a craft consisting in the attempt to

replace a written message and/or statement in one language by the same message

and/or statement in another language.” (1988:7). In this definition, Newmark

focuses only on the replacement of written message, and/or statement without

considering the style used in the text.

Bell states “translation is the expression in another language (or target

language) of what has been expressed in another, source language, preserving

semantic and stylistic equivalences” (1991:5). Larson defines that, “Translation

consists of transferring the meaning of the source language in the receptor

language.” (1984:3). Based on the explanation above, the TL should have the

same meaning as what is brought in the SL.

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B. Types of Translation

According to Nababan (2003), there are ten types of translation. The use of

different types of translation is caused by several factors, which are (1) the

differences of the source and target language systems, (2) the differences of the

fields of the translated texts, (3) consideration that translation is a means of

communication and (4) the differences of the purposes of the translation.

1. Word for word translation

Using this type of translation, translator only replaces source language

words with their equivalences in target language. The arrangement of the words in

source text is the same as that in the target text.

Example: I bought a book yesterday.

Saya membeli sebuah buku kemarin.

The example above shows that the sentence is translated word by word.

It can happen because the sentence structure between source text and target text

are the same.

2. Free translation

Catford states “A free translation is always abounded-equivalences shunt

up and down the rank scale, tend to be at the higher ranks sometimes between

larger units than the sentences” (1965:25). In free translation, equivalences are not

achieved at word or sentence level but at a paragraph or a discourse level.

Translator has to be able to understand the whole message of a paragraph or a

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discourse thoroughly and then express the message in target language. Free

translation is usually used to translate idiomatic expressions and proverbs.

Example: killing two birds with one stone

Sekali merengkuh dayung, dua tiga pulau terlampaui

The example above shows that in free translation the priority is the

equivalence of the meaning rather the form. The translator freely expresses the

translated sentences in target language as long as the message is currently

transferred.

3. Literal translation

Literal translation is similar to word for word translation but they are

different in the way that in this type of translation, translator does not simply

replace words in source language with their equivalences but he or she also

adjusts the arrangement of the words to word arrangement rule in the target

language.

Example: good time

waktu yang tepat

In this translation, the adjective “good” which comes before the noun

“time” is re-arranged and placed after the noun in target language. It is because in

Indonesian language, the rule for this kind of construction is that the adjective

comes after the noun.

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4. Dynamic translation

In this type of translation, message from source language is expressed in

natural expressions in target language.

Example: the writer has organized his book for one year

penulis telah menyusun bukunya selama satu tahun

In this translation, the translator prefers to translate “organized” into

“menyusun” rather than into “mengorganisasi”. It makes the translation sound

natural.

5. Pragmatic translation

This type of translation emphasizes on the accuracy of the message in

target language which is appropriate with the use in the source language.

Pragmatic translation does not focus on the aesthetic aspect of the sentences in the

source language.

Example: for baby: after bathing, dust generously over the skin, taking

special care where the skin folds and creases. Use after baby’s

bath and every change

(untuk bayi: taburkan bedak pada seluruh kulit sehabis mandi,

terutama pada bagian-bagian lipatan kulit. Gunakan pada

setiap menggantikan popok dan sehabis mandi).

(Nababan, 2003:35)

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6. Aesthetic-poetic translation

This type of translation is different from pragmatic translation. If

pragmatic translation emphasizes only on the accuracy of the message, aesthetic-

poetic translation emphasizes on the accuracy of the message as well as the

impression, emotion and feeling aroused by the text and the beauty of the

language.

Example: Di luar salju terus. Hampir pagi.

Tubuhmu terbit dari berahi.

Angin menembus. Hilang lagi.

Nafasmu membayang dalam dingin. Mencari.

Outside snow falls. Almost morning.

Your body shaped in sensual feeling.

The wind pierces. And is clearing.

Your breath a shadow in the cold. Searching.

(Machali, 2000:80)

The translation of the poetry attempts to preserve the beauty of the text by

producing regular rhymed –i in the target text. Also, the translator emphasizes

his/her intention in the accuracy and the diction of translation due to the feeling,

emotion, and impression from the source text.

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7. Linguistic translation

Linguistic translation refers to translation attempting to make implicit

linguistic information in source language become explicit. This type of translation

uses back-transformation and meaning component analysis to fulfill its objective.

Translator finds linguistic information, such as morphemes, words, phrases,

clauses and sentences and makes the information explicit.

Example: They are sailing boats. (a)

They are now sailing boats. (b)

They are the sailing boats. (c)

Sentence (a) is ambiguous since it may mean a declarative sentence stating

that “they”, referring to persons, are sailing boats on water at present and it may

also mean a declarative sentence indicating several sailing boats. Sentences (b)

and (c) make the information explicit.

8. Communicative translation

Like the other types of translation, communicative translation emphasizes

on the transfer of message. Newmark in Nababan (2003) regards translation as

social phenomenon having multi-dimension. Source and target languages, culture,

source text writer, translator and readers need to be considered. Communicative

translation also concerns about the effectiveness of the translation and the effect it

arises (p. 29).

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Example: Open the door, please.

Open the door!

Both sentences have different effects and will result different response.

Therefore, they must be translated into different expressions. They should be

translated into “Tolong tutup pintunya.” and “Tutup pintunya!”.

C. Equivalence

A translation activity cannot be separated from finding out the source language equivalences in the target language. Equivalence, as pointed out by Barnstone in Nababan (2003:99), is the core of translation. It means that transferring message of a text is always dealt with equivalence.

1. Equivalence at word level

The first attention of the translator, in translation process, is related to the meaning of word in the source language text. Word, defined by Bolinger and Sears in Mona Baker (1992:11), is the smallest unit of language that can be used by it. This is possible because every word conveys a certain meaning. As the smallest unit of language conveying the meaning, words become a starting point for the translator to understand the whole message of the text. Equivalence at word level is related to the lexical meaning of a word. This lexical meaning can be thought as the specific value the word has in a particular linguistic system. It means that every word has specific meaning that differentiates it from the other words.

2. Equivalence above word level

When co-occur with other words, words can reproduce a particular meaning in form of phrase, expression or idiom and these are called collocation. Collocation explained by Mona Baker (1992:47) as the tendency of certain words to co-occur regularly in a given language, has a pattern or form, which is arbitrary in building a certain meaning. However, when two words collocate, the relationship can hold among all or several of their various forms, combined in any grammatically acceptable order. Dry, for instance, can be easily explained what it means and it is potential to collocate with such words as voice, humour becoming new words with new meaning such as dry voice, dry humour. The collocational meaning of dry voice is different from the prepositional meaning of dry and voice. Dry voice means ‘cold speaking in the sense of not expressing emotion. The translator will be considered fail to catch the meaning of dry voice if he/she translates this as ‘a voice which is not moist’. Generally speaking, collocations are fairly flexible patterns of language, which allow several variations in form. In it’s extend, collocation produces idiom such as good morning, merry Christmas.

3. Grammatical equivalence

Grammar, explained by Mona Baker (1992:83), is organized among two main dimensions; morphology and syntax. The first one covers the structure of words, the way in which the form of a word changes to indicate specific contrast in the grammatical system. The last covers the grammatical structure of groups, clauses, and sentences. The syntactic structure of a language determines certain restrictions on the way messages may be organized in that language. Grammatical equivalence is dealing with how the translator transfers the grammatical meaning of the source language to the target language. This is how he/she interprets, for instance, the use of tense, number or gender into another language.

D. Translation Techniques

As translator, in translating process the translator should apply techniques

to produce a good translation, the perception of translation as the final product of

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the translated text in relation to the source text. Translation technique is a specific

textual procedure for translating a particular structure or linguistic item.

Translation technique is the special techniques used by translators when

transferring the message of the source language into the target language, includes

the choice of equivalents. Translation technique is a procedure to analyze and

classify how the translation equivalence happens and to be applied on different

linguistic unit. (http://www.emanueltov.info/docs/papers/16.trans.techn.1999.pdf)

1. Addition.

Addition can be divided into two types: the first is addition for

structural reason and the second is addition for semantic reason. Addition

for structural reason means that the translator adds certain word in the

target text due to the difference structure of the source and target language.

The second type is addition for semantic reason. This technique is

applied for the sake of meaning clarity. The translator, in this case, adds

some additional information to the text because of the consideration that

the reader would need that information and without it they would have

difficulties in understanding the text. The additional information can be

put within the text, at the bottom of the text as notes, at the end of the

chapter or at the end of the book (Newmark, 1988).

Example:

Source Text: The skin, which is hard and scaly, is grayish in color,

thus helping to camouflage it from predators when underwater.

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Target Text: Kulitnya, yang keras dan bersisik, berwarna abu-abu.

Dengan demikian, kulit ini membantunya berkamuflase, menyesuaikan diri

dengan keadaan lingkungan untuk menyelamatkan diri dari predator,

hewan pemangsa, jika berada di dalam air.

(Taken from Suryawinata, 2000: 75).

In above example, the translator gives additional information to the

biological term in the text. Translator adds the phrase menyesuaikan diri

dengan keadaan lingkungan to the word camouflage and hewan pemangsa

to explain the word predator.

2. Borrowing or borrowing plus explanation.

This technique is particularly common in dealing with culture-specific items and modern concepts. The loan word with explanation is very useful when the word in question is repeated several times in the text. Once explained, the loan word can then be used on its own; the readers can understand it and is not distracted by further lengthy explanation. Mona Baker (1992).

Example: SL: Transferring and exchanging information

Bluetooth wireless technology

TL: Memindahkan dan saling menukar informasi

teknologi tanpa kabel Bluetooth

Bluetooth is a new technology and it does not have the equivalence in Indonesian language. The way to solve the problem is by borrowing the word without translating it.

3. Naturalization.

This technique succeeds transference and adapts the SL word first to the normal pronunciation, then to the normal morphology (word-forms) of the TL (Newmark, 1988).

Example: SL: Taxi TL: Taksi

SL: Mall TL: Mal

4. Literal Translation.

Literal translation is a translation that follows closely the form of the

source text, known as word-for-word translation (Larson: 1984). It focuses

on the form and structure of the source text.

Example:

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SL : I bought a book yesterday.

TL :Saya membeli sebuah buku kemarin.

5. Deletion (omission).

This technique may sound rather drastic, but in fact it does no harm to omit translating a word or expression in some contexts. If the meaning conveyed by a particular item or expression is not vital enough to the development of the text to justify distracting the reader with lengthy explanations, translators can and often do simply omit translating the word or expression in question.

Example: SL : Mobile phone can be used, for example, to send

message and to make call.

TL : Telepon genggam dapat digunakan untuk mengirim

pesan dan menelepon.

The above example shows that the word “for example” is omitted. It

does not distort the message since the word omitted does not give a

significant meaning.

6. Free Translation.

Free translation is translation technique that places meaning as the highest priority. It means that the translator task is to deliver meaning exactly the same as the original although with totally different structure and wording.

Example: SL : His heart is in the right place.

TL : Dia baik hati. (Nababan, 2003: 33).

7. Translation Shifts.

This technique is used in order to overcome the problem related to

different language systems. The actual term shift was introduced by

Catford (1965), who distinguishes formal correspondence, which exists

between source and target categories that occupy approximately the same

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place in their respective systems, and translational equivalence, which

holds between two portions of texts that are actually translations of each

other. A shift has occurred if there are “departures from formal

correspondence” (p.73) between source and target texts, i.e. if translational

equivalents are not formal correspondents.

According to Catford, there are two major types of shifts: level shifts and category shifts. Level shifts are shifts between grammar and lexis, e.g. the translation of verbal aspect by means of an adverb or vice versa. Category shifts are further subdivided into structure shifts (e.g. a change in clause structure), class shifts (e.g. a change in word class), unit shifts (e.g. translating a phrase with a clause), and intra-system shifts (e.g. a change in number even though the languages have the same number system). (Cyrus: 2006)

a. StructureShifts.

This type involves a grammatical change between the structure of the ST and TT. Catford (1965) states that this shift, can occur at all rank of grammar; at group rank and at clause ranks.

Example:

SL: green shirt

TL: kaos hijau

The example of SL is a noun phrase and the structure is M (green) and H (shirt), whereas the TL noun phrase structure is H (kaos) and M (hijau). The example above shows the structural shift is found at the group rank. The structure of English noun phrase will automatically change as it shown in the example above, if it is translated into Indonesian.

Example:

SL: He took that stone

S F/P C

TL: Batu itu diambil-nya

C P S

From the example above, the syntactic function of the SL clause is: ‘he’ as Subject, ‘took’ as finite/predicator, ‘that stone’ as complement. Meanwhile, in TL there are some changes. The TL clause syntactic function is: “batu ini” as subject, “diambil” as predicator, “-nya” as complement. In SL, the position of the word ‘he’ is as subject. The word ‘he’ is replaced by the word “-nya” in TL and it has position as complement. In SL, the phrase ‘that stone’ functions as complement. Meanwhile, the phrase itself changes into the phrase “batu ini” in TL and its position as subject. The syntactic function of the SL clause is S - F/P - C, whereas the syntactic function of the TL clause is C - P - S. The example shows a structural shift at clause rank.

b. Class shifts or Category shift).

Translation shift is called class shift when a SL item is translated with a TL item which belongs to different grammatical class. As stated by Catford (1965) class shift occurs when the translation equivalent of a SL item is a member of a different class from the original item.

Example:

SL: He’s in danger

TL: Dia dalam keadaan bahaya

(Taken from Simatupang, 2000:91)

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The word “danger” in the SL has syntactic category as Noun, and translated/changes into “bahaya” in the TL. The word “bahaya” in syntactic category is an adjective. The example shows a class shift from noun into adjective.

c. Unit shifts (is similar to level shift; is similar to rank shifts).

This type of translation shift involves change in rank. As stated by Catford (1965:79) that unit shift occurs when the translation equivalent of a unit at one rank in the SL is a member of a different rank in the TL.

Example:

SL: He walks slowly

TL: Dia berjalan dengan lamban

From the example, it can be seen that the adverb “slowly” in the SL is replaced by the prepositional phrase “dengan pelan” in the TL. There is unit shift from word “slowly” into “dengan pelan”.

E. Translation Quality Assessment

Nababan (2003: 83) states that “assessing the quality of a translation

means criticizing a literature work.” As there is neither a definitive reading of a

text or a perfect rendering which achieves the goals of ST, translation quality

assessment and criticism could go forever. The aim of criticizing a literature work

is to find out the strengths and the weaknesses of a translation.

(http://www.erudit.org/revue/meta/2000/v45/n3/001878ar.pdf)

Larson (1998) mentions that a translation must be examined since a

translator needs to make sure the accuracy, the clarity and the nature of a

translation. This is similar to the procedure employed by Nababan (2004) in his

research on translation process, practices, and products of professional Indonesian

translator. Indirectly, a good translation shows that the translator has a good

capability to translate and vice versa. (Nababan, 2003) The quality assessment

covers three points; readability, acceptability and accuracy. Nababan (2004) adds

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that acceptability as the third factor that is considered important in assessing

translation quality.

1. Accuracy

Shuttleworth and Cowie (1997) define accuracy as a term used in translation evaluation to refer to the extent to which a translation matches its original. The accuracy of the message is an important thing in translation. Accuracy is a factor determining the quality of translation. Accuracy also means that the message of the source text is transferred into target text correctly and the translation can be understood by the target readers easily. A translation is considered to be accurate if it conveys the meaning of the source language to the target language correctly. The target readers of the translation should have the same interpretation, information, understanding, and feeling as the writers or the readers from the source of the texts.

From the statement, it can be seen that preservation of meaning is a very

important aspect in translation. The sameness in meaning is one of the factors

determining the quality of a translation. Therefore, a translator has to be able to

preserve the meaning or message of the original text.

In conclusion, to be able to produce accurate translations, a translator has

to preserve the meaning contained in the source text, attempt to create equivalent

response and purpose through the translation he or she produces as well as

produce translations which have similar style and manner of writing as the source

texts.

2. Acceptability

Acceptability of a text refers to the natural “feel” of the translation. A

translation which leans toward acceptability can thus be thought as fulfilling the

requirement of “reading as an original” that is written in target language rather

than that of “reading as the original”. (Shuttleworth and Cowie, 1997)

A translation must be acceptable for its readers. A translator should be able

to produce translation which is natural according to target language system. A

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good translation is a translation which does not replicate the characteristics of

source language (Sadtono, 1985). A translator should express the message he or

she translates appropriate with the literary norms of target language.

(Suryawinata: 2000).

3. Readability

“Readability refers to how naturally and easily a translation can be read.”

(www.geocities.com). Readability is important in translation because translation

cannot be separated from reading activity (Nababan: 2003). Therefore, a translator

has to pay attention to this aspect. It is because readability influences the readers’

understanding of the message of a translation. A translation will be easier to

understand if it is easy to read.

There are many factors influencing the readability of a text. Basically,

there are four main factors. The first factor is the diction used in a text. This factor

includes the use of new words, foreign words and ambiguous words. The second

one is related to sentences which a translator writes. This factor includes (1) the

use of foreign sentences, ambiguous sentences and incomplete sentences, (2) the

length of the sentences and (3) the complexity of the sentences. The next factor is

how the translator arranges the idea of his or her translation. The last factor

includes other factors than which have been mentioned. They are (1) the content

of a text, (2) the appearance of a text and (3) the ability of both the translator and

the reader (Nababan: 2003).

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F. Friendster

Friendster is an online social networking service. It was founded in

California by Jonathan Abrams in the year of 2002. Friendster is a privately

owned internet social networking website and the first online social network.

Its headquarters are in Mountain View, CA, US. Friendster is one of the

oldest and first of the popular social networking sites boom. The concept of

friendster is based on a circle of friends and various friends’ techniques for

individuals to social network within virtual communities. Friendster is focused on

helping people meet new friends, stay in touch with old ones and sharing online

content and media. The website is also used for dating and discovering new

events, bands, hobbies, and more. Users can share content including videos,

photos, messages and comments with friends via their profile and their network.

Friendster is widely used in Asia. It has over 50 million users worldwide.

MySpace took over Friendster's number one position in popular social networking

sites when it was introduced in 2004. Now the social networking site known as

friendster has competition from every angle. There are new social networking

sites growing everyday. Averages of 90% of young people are participating in

social networking sites daily. Google offered to buy the social network called

Friendster in the year of 2003 but Friendster declined. Today, that decision not to

sell to Google is considered as one of the biggest financial mistakes to many

individuals. The amount of 53 million was funded to Friendster by Kleiner

Perkins Caufield & Byers and Benchmark Capital in the year of 2003. Friendster

xxxv

was awarded the prestigious patent in the year of 2006 for their method of

calculating and displaying relationships in a social network.

It was dubbed with the name of Web of Friends due to the circles

displayed of individual friends profile pictures. Each circle has a line drawn

similar to a web connecting them to another contact on your friend list. It was

very creative and crafty of them. Friendster is available in many different

languages. Friendster has a language link that can change the text displayed on the

site to Chinese, Japanese, Korean, Thailand, Indonesia, or Spanish for other users.

(http://www.webupon.com/Social-Networks/The-History-of-Friendster.102940)

G. Website Localization

With the rise in ownership of computers and internet usage growing daily,

the internet is fast becoming the primary port of call for information, shopping

and services. In addition, those computer and internet users are increasingly from

non-English speaking countries. At the end of 2002, it was estimated that 32% of

internet users were non-native English speakers. This figure is constantly rising.

In response, businesses have quickly become aware of the benefits of website

localization.

Website localization is the process of modifying an existing website to

make it accessible, usable and culturally suitable to a target audience. Website

localization is a multi-layered process needing both programming expertise and

linguistic/cultural knowledge. If either is missing, the chances are that a

localization project will encounter problems. In the majority of cases it is the lack

xxxvi

of linguistic and cultural input that lets a website localization project down. In

order to give an insight into the impact culture has on website localization the

following examples depict areas in which a solid understanding of the target

culture is necessary.

Translating a website from English into another language is not as simple

as it may appear. There are numerous factors that have to be taken into

consideration when translating a websites’ content. One must analyze the style of

the language and the target audience. If the audience is foreign business

personnel, the vocabulary, grammar and punctuation must reflect this. If the

audience is informal or youth orientated then a more relaxed language must used.

Just as we in the UK would identify the difference between a site using ‘posh

English’ and ‘street English’, other cultures will have the same perceptions of

language. Using the wrong language for the wrong reader in your localization

project will lead to a misunderstanding of the site or company.

It is essential to assess what information is necessary to carry over into the

new site. Do not assume that all information on the English site is automatically

transferred over. One must evaluate the target culture and society.

(http://ezinearticles.com/?Culture-and-Website-Localization&id=832)

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CHAPTER IV

DATA ANALYSIS

A. INTRODUCTION

Chapter four presents analysis data to answer the problem statements as

mentioned in the chapter one. This chapter consists of two main parts. The first

part is the introduction, which provides the illustration of what would be analyzed

in this research. The second part is the analysis of the data.

First, the analysis deals with the techniques used by the translator in

translating the friendster website. Then, the second analysis would be about the

quality of the translation. It presents the analysis of the accuracy, acceptability,

and readability of the translation. It would provide the findings of the research

based on the questionnaires which were completed by the raters and respondents.

B. ANALYSIS

This section presents the techniques applied by the translator to translate

the website in English version into Indonesian version. There are some techniques

found in translating the website.

1. Translation Techniques

The first part of this chapter is analysis about the translation techniques

that are used by the translator in translating the friendster.com. After analyzing all

of the data in both texts, the researcher finds ten translation techniques used by the

xxxviii

translator to translate text from source language into the target language. They are

addition, borrowing, naturalization, literal, deletion, free, and structural shift from

plural into singular, structural shift from modifier-head (M-H) into head-modifier

(H-M), unit shift from phrase into word, and unit shift from word into phrase.

1. 1. Addition.

Addition is a technique where the translator adds some information in

the translation to give a clearer translation to the reader. There are 7 data that are

translated using addition technique.

Example from the data:

Example 1:

076. Friend requests

076. Permintaan Menjadi Teman

Example 2:

102. Newsletter updates

102. Pembaruan Buletin Berkala

Example 3:

167. Current courses

167. Kelas yang diikuti saat ini

The examples above show that there are additions of some words. Those

examples use addition translation technique for semantic reason, since the purpose

of the addition is to make the translation more easily to be understood by the

users. The translator put the addition words ‘menjadi’, ‘berkala’, and ‘yang

diikuti’, within phrases of the examples. The additions of words, however, do not

change the message.

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The data numbers of this technique can be seen in the table:

Table 4.1.1

Addition

Technique Data numbers Total

Addition 048, 064, 076, 084, 102, 144, 167 7

1. 2. Borrowing or borrowing plus explanation.

In this technique, the translator transfers the words from the source

language into the target language without any modification. This technique is

usually used to translate specific terms, names, places, and scientific terms. The

translator can borrow the SL words and give explanation about the borrowed

words. There are 21 data that are translated using borrowing technique.


Example 1:

007. Email address

007. Alamat email

Example 2:

119. Your URL

119. URL Anda

Example 3:

152. Friendster skins

152. Skin friendster

From the examples above, it can be seen that the translator borrowed some

words from the source language in the target language. The examples show that

the translator borrowed the words ‘email’, ‘URL’, and ‘skin’. In this example, the

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word ‘skin’ can be translated into “kulit” in the TL, but the users may not be

familiar with the word “kulit”. It makes the translator prefers to keep the original

word.


Table 4.1.2

Borrowing or borrowing plus explanation


Borrowing or

borrowing

plus

explanation

007, 018, 056, 065, 070, 071, 072, 087, 094,

098, 101, 110, 114, 119, 125, 131, 147, 155,

160, 163, 169

21

1. 3. Naturalization.

This technique succeeds transference and adapts the source language word,

first to the normal pronunciation, then to the normal morphology of the target

language. There are 33 data that are translated using naturalization technique.

Examples from the data:

Example 1:

022. NEW Bulletins

022. Buletin BARU

Example 2:

027. NEW Horoscope

027. Horoskop BARU

Example 3:

132. Zodiac sign

154. tanda zodiak

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From the three examples above, it can be seen that the translator employed

naturalization in translating some words. In the first example, the words

‘bulletins’, ‘horoscope’, and ‘zodiac’ are absorbed into Bahasa Indonesia as

“buletin”, “horoskop”, and “zodiak”. The ST words are adopted into Bahasa

Indonesia by changing some consonants of the source language words. To

translate word “bulletin”, the consonants of double -l- are changed into one -l- to

adjust the Indonesian language system. In the word ‘horoscope’ and ‘zodiac’, the

consonant -c- is changed into -k-, also for the word ‘horoscope’, the last vowel –e

is deleted.


Table 4.1.3

Naturalization


Naturalization

004, 019, 022, 027, 028, 039, 052, 058, 059,

060, 065, 079, 082, 083, 085, 089, 091, 097

099, 105, 106, 109, 112, 118, 125, 126, 127,

129, 132, 147, 148, 159, 162

33

1. 4. Literal Translation.

Literal translation is a translation that follows closely the form of the

source text, known as word-for-word translation (Larson 1984:10). It focuses on

the form and structure of the target text. It is a SL oriented translation technique.

There are 34 data that are translated using literal technique.

xlii


Example 1:

013. About us

013. Tentang kami

Example 2:

017. Policy privacy 017. Kebijakan privasi

Example 3:

093. Two degrees

093. Dua gelar

From those three examples, it can be seen clearly that the translator applies

the literal technique by translating the phrases word for word and keep the

structure of sentence of the SL.


Table 4.1.4

Literal


Literal

002, 012, 013, 014, 017, 018, 028, 032, 036,

040, 042, 043, 044, 046, 049, 059, 113, 115,

117, 118, 120, 133, 134, 135, 138, 141, 142,

143, 153, 154, 157, 161, 166

34

1. 5. Free Translation

Free translation is translation technique that places meaning as the highest

priority. It means that the translator task is to deliver meaning the same as the

xliii

original although with very different structure and wording. There are 10 data that

are translated using free translation technique.

Example from data:

Example 1:

016. Terms of service

016. Syarat dan layanan

Example 2:

069. Maiden Name

069. Nama gadis

Example 3:

167. Current courses

167. Kelas yang diikuti saat ini

Those three examples show that the translator uses free translation to

translate the phrases. As seen in the example 1, the translator translates ‘terms of

service’ freely into “Syarat dan Layanan” rather than “Ketentuan Layanan”

which is the literal translation of ‘terms of service’. In the example 2, the

translator translates ‘maiden’ freely into “gadis”. In the example 3, the translator

translates ‘courses’ freely into “kelas”.


Table 4.1.5

Free Translation


Free

Translation

016, 017, 035, 037, 069, 090, 103, 106, 136,

166 10

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1. 6. Translation Shifts.

This technique is used in order to overcome problems related to the

different language system between SL and TL. Shift is a translation technique

involving a change in the grammar from the source language into the target

language. There are two types of shift found in the data, they are structure shifts

and unit shifts.

a) Structure Shifts.

This type involves a grammatical change between the structure of the SL

and TL. Catford (1965:77) states that this shift, in grammar, can occur at all rank;

at group rank and at clause rank.

1. Shift from Plural into Singular.

This is the kind of shift that changes the structure of the word and phrase

of the SL after being translated into TL from plural into singular. There are 35

data that are translated using this technique.

Example 1:

022. NEW Bulletins

022. Buletin BARU

Example 2:

123. LâmβânK's Friends

123. Teman dari LamBank

Example 3:

129. Favorite musics

129. Musik favorit

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In the three examples above, some plural forms are changed into singular

forms. In datum number 022 the translator changes the words ‘bulletins’ (plural)

into “bulletin” (singular). The same case also happen in the data number 123 and

129 where the words ‘friends’ and ‘musics’ (plural) are translated into “teman”

and “musik” rather than “teman-teman” and “music-music”, the plural forms in

Indonesian language.

2. Shift from Modifier - Head (M - H) into Head - Modifier (H - M).

This kind of translation shifts that change of the structure of phrase

because of different system of grammar between SL and TL. There are 101 data

that are translated using this technique.

Example 1:

007. Email address à Alamat Email

H M M H

Example 2:

073. Continent List à Daftar Benua

H M M H

Example 3:

170. School name à Nama sekolah

H M M H

Those examples of SL are phrases with modifiers ‘address’, ‘list’, and

‘name’, while the heads are ‘email’, ‘continent’, and ‘school’. The TL phrase

structures are different in which the modifiers are “alamat”, “daftar”, and

“nama”, while the heads are “email”, “benua”, and “sekolah”. The example

above shows the structural shift at the group rank. The structure of English noun

xlvi

phrase will automatically change if it is translated into Indonesian as shown in the

example above.

The three examples above show that the position of adjective is changed.

In English structure, adjective functions as modifier, so its position must be in

front of the head. It is different from the structure of Bahasa Indonesia where

adjective must be preceded by noun. Thus, the translation of email address,

continent list, and school name (M-H) are alamat email, daftar benua, and nama

sekolah (H-M).

b) Unit Shifts.

This type of translation shift involves change in rank. As stated by Catford

(1965:79) that unit shift occurs when the translation equivalent of a unit at one

rank in the SL is a member of a different rank in the TL.

1. Shift from word into phrase.

This is the kind of shift that changes the rank from word into phrase. There

are 11 data that are translated using this technique.

Example 1:

053. College search

113. Pencarian perguruan tinggi

Example 2:

113. More searches

113. Lebih banyak pencarian

In datum number 053, it can be seen that the word ‘college’ is

translated into a phrase “perguruan tinggi”. The occurrence of this technique can

xlvii

also be seen in datum number 113 where the word ‘more’ is translated into “lebih

banyak”.

Table 4.1.6

Translation Shift


Structure

Shifts

Shift from

plural into

singular

002, 005, 009, 020, 022, 023, 024, 025, 031, 038, 041, 045, 048, 058, 061, 065, 066, 067, 076, 077, 083, 092, 094, 096, 097, 099, 100, 101, 102, 122, 123, 125, 127, 134, 150

35

xlviii

Shift from (M-

H) into (H-M)

001, 003, 004, 005, 006, 007, 008,

009, 010, 011, 015, 019, 020, 022,

023, 024, 025, 026, 027, 029, 030,

031, 033, 034, 035, 037, 038, 039,

041, 045, 047, 048, 050, 051, 052,

053, 054, 055, 056, 057, 058, 060,

061, 062, 065, 066, 067, 068, 070,

071, 072, 073, 074, 075, 076, 077,

078, 079, 080, 081, 082, 083, 084,

085, 086, 087, 088, 089, 090, 091,

092, 093, 094, 095, 096, 097, 098,

099, 100, 101, 102, 103, 104, 105,

106, 107, 108, 109, 110, 111, 112,

114, 116, 119, 121, 122, 123, 124,

125, 126, 127, 128, 129, 130, 131,

132, 136, 137, 139, 140, 144, 145,

146, 147, 148, 149, 150, 155, 156,

158, 159, 160, 162, 163, 164, 165,

168, 169, 170, 171, 172

138

Unit Shifts

Shift from word

into phrase

021, 043, 053, 100, 113, 123, 135,

145, 146, 164, 165 11

Total 163

Here is the table that shows the complete distribution of translation

techniques of the website friendster.com.

Table 4.1.7

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Translation Techniques

No Techniques Number of data

Percentage

1 Addition 7 2.76 %

2 Borrowing or borrowing plus explanation 21 7.24 %

3 Naturalization 33 11.38 %

4 Literal 34 11.72 %

5 Free Translation 10 3.45%

6 Structure Shifts:

Shift from plural into singular 35 12.07 %

Shift from (M-H) into (H-M) 138 47.59 %

Unit Shifts:

Shift from word into phrase 11 3.79 %

Total 299 100%

The number of the data is more than 172 since most of the data are

applied more than one technique.

From the research, it can be seen that translation techniques that is most

frequently used by the translator is structure shift from (M-H) into (H-M). It has

been used to translate 138 data or 47.59% from the overall data. It is followed by

structure shift from plural into singular that has been used to translate 35 data or

12.07% from the overall data. It followed by literal translation that has been used

to translate 34 data or 11.72% from the overall data, then naturalization with 33

data or 11.38% from the overall data. The next is borrowing or borrowing plus

explanation with 21 data or 7.24% from the overall data, then unit shift from word

into phrase 11 data or 3.79% from the overall data, free translation with 10 data or

3.45% from the overall data, , and addition with 7 data or 2.76% from the overall

data.

l

2. Translation Quality Assessment

2.1. Accuracy

This section presents the analysis of the accuracy level of the translation of

the website friendster.com.

The researcher involves three raters who have certain qualifications to

assess the accuracy and the acceptability of the translation. The three raters were

asked to complete the questionnaires to determine the accuracy and acceptability

of the message transfer of the translation. The questionnaires are in form of close

and open-ended questionnaire. In this form of questionnaires, firstly, the raters

determine the accuracy of the translation by giving mark to the translation and

then, secondly, they may give their comments or suggestions related to the

accuracy of message transfer of the translation.

The accuracy of message transfer of the translation is measured based on

the following scale:

Scale Description

1 Accurate, the content of the original text is perfectly conveyed into

the target text. The translation is clear and no rewriting is needed.

2

Less Accurate, the content of the original text is less perfectly

conveyed into the target text. The translation can be clearly

understood, but some rewriting and some changes in word order are

needed.

3 Inaccurate, the content of the original texts is not perfectly conveyed

into the target text. There are some problems with the choice of lexical

li

items and with the relationships between phrase and sentence

elements.

4 Very Inaccurate, the content of the original texts is not conveyed at

all, .e. it is omitted or deleted.

After the raters complete all of the questionnaires, the researcher makes

statistical calculation to determine the mean of each datum with a formula.

Data Number

Rater 1 Rater 2 Rater 3 Total Mean

01 score score score total Total score Total raters


When the statistical calculation is finished, the data are classified into four

groups, as can be seen below:

1. Classification A: Accurate, includes the data with score mean 1.00.

2. Classification B: Less Accurate includes the data with score mean

1.01 – 2.00.

3. Classification C: Inaccurate, includes the data with score mean 2.01 –

3.99.

4. Classification D: Very Inaccurate includes the data with score mean

4.00.

Based on the table of accuracy in appendix, of 172 data, 146 data (84.88%)

were categorized in classification A or accurate, 26 data (15.12%) were

lii

categorized in classification B or less accurate, with no data that was categorized

in classification C or inaccurate and D or very inaccurate.

Mean of all data = : total data

= : 176

= 1.07 (B)

It means that equally, the accuracy level of the website is B / Less

accurate.

Table 4.2.1

The table distribution of accuracy level:

Classification Data Number Total

A

001, 003, 004, 005, 006, 007, 008, 009, 010, 011, 012, 013, 014, 017, 018, 019, 020, 021, 022, 024, 025, 026, 027, 028, 029, 030, 031, 032, 034, 035, 036, 037, 038, 039, 040, 041, 042, 043, 044, 045, 046, 049, 050, 051, 054, 055, 056, 057, 058, 059, 060, 061, 063, 065, 066, 067, 068, 069, 070, 071, 072, 073, 075, 076, 077, 078, 079, 080, 083, 085, 086, 087, 089, 090, 091, 092, 093, 094, 095, 096, 097, 098, 099, 100, 101, 102, 105, 106, 107, 110, 111, 112, 113, 114, 116, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 141, 142, 143, 144, 145, 146, 147, 148, 149, 151, 152, 153, 154, 155, 156, 157, 159, 160, 161, 162, 163, 164, 165, 167, 168, 169, 170, 171, 172

146

B 002, 015, 016, 023, 033, 047, 048, 052, 053, 062, 064, 074, 081, 082, 084, 088, 103, 104, 108, 109, 115, 117, 139, 140, 150, 158

26

C 0 0

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D 0 0

Total 172

1. Classification A: Accurate Translation.

All data classified in this classification are accurate. The mean score of the

data is 1.00. There are 146 data (84.88%) considered to be accurate. It means

content of original text is accurately conveyed and it does not need any rewriting.

Some of the data are presented below:

Example 1:

015. My blocked user

015. Pengguna saya yang diblokir

Example 2:

093. Two degrees

093. Dua gelar

Example 3:

116. Activity partners

116. Mitra aktivitas

Those three examples are considered to be accurate. All of the three raters

gave score 1.00. Datum 015 applies structure shift from H–M into M–H

translation technique. Datum number 093 applies structure shift from plural into

singular translation technique. Datum 116 applies structure shift from H–M into

M–H and structure shift from plural into singular translation technique. The data

are accurate according to three raters with the mean score 1.00 because the

meaning of the sentences are accurately conveyed into the TL.

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2. Classification B: Less Accurate.

All data classified in this classification are less accurate. The mean score

of the data is 1.01 into 2.00. There are 26 data (15.12%). The data are classified

less accurate, if the content of original text is less accurately conveyed and some

rewritings are needed.


Example 1:

023. NEW Birthdays

023. Ulang Tahun BARU

Different judgment is given toward this translation. Both of two raters,

rater 2 and 3, gave score 1, while the rater 1 gave score 2. The judgment result for

this translation is 1.33 for the mean of translation. Rater 2 and rater 3 argue that

the message of this text is accurately conveyed and it has appropriate meaning of

the text. Different opinion proposed by rater 1. According to the rater 1, the

message of the original text is not accurately conveyed.

Example 2:

139. Dating Men

139. Pria Berkencan

Different judgment was given toward this translation. All of three raters

gave different opinion about the score of accuracy of this translation. Rater 1 gave

score 3, rater 2 gave score 2, and rater 3 gave score 1. The judgment result for this

translation is 2.00 for the mean of translation. Rater 1 argued that the message of

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this text is inaccurately conveyed and it has appropriate meaning of the phrase.

Different opinion is proposed by rater 2 and rater 3. According to the rater 2, the

accuracy level of this translation is less accurate, and the rater 3 argues that this

translation is accurate. In addition, rater 1 and 2 mentioned that there is a

rewriting needed. Rater 2 gave opinion that the phrase ‘dating men’ should be

translated into “pria untuk teman berkencan”rather than “pria berkencan”. The

researcher, then, agree with the rater 2’s opinion. It really needs a rewriting for

this translation.

Example 3:

140. Dating Women

140. Wanita berkencan

Different judgment was given toward this translation. All of three raters

gave different opinion about the score of accuracy of this translation. Rater 1 gave

score 3, rater 2 gave score 2, and rater 3 gave score 1. The judgment result for this

translation is 2.00 for the mean of translation. Rater 1 argued that the message of

this text is inaccurately conveyed and it has appropriate meaning of the phrase.

Different opinion is proposed by rater 2 and rater 3. According to the rater 2, the

accuracy level of this translation is less accurate, and the rater 3 argues that this

translation is accurate. In addition, rater 1 and 2 mentioned that there is a

rewriting needed. Rater 2 gave opinion that the phrase ‘dating women’ should be

translated into “wanita untuk teman berkencan”rather than “wanita berkencan”.

2.2. Acceptability

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This section presents the analysis of the acceptability level of the

translation of the website of friendster.com. Acceptability means to produce

translation which is natural according to target language system. A translator

should express the message he or she translates appropriate with the literary

norms of target language.

The norms include sentence structures, grammars, and dictions etc. Thus,

to produce acceptable translations, a translator must express the transferred

message in natural expressions in target language.

The acceptability of message transfer of the translation is measured based

on the following scale:

Scale Description

1

Acceptable, the translation sounds natural and appropriate with the

grammar structure of the target texts, almost does not feel like

translation.

2

Less Acceptable, the translated texts sound like translation. There are

some displeasing in terms of the words, phrases, and sentences in the

target text, but almost sounds like natural.

3 Inacceptable, the translated texts extremely sounds like translation

and feel displease as Indonesian texts.

After the raters complete all of the questionnaires, the researcher makes

statistical calculation to determine the mean of each datum with a formula.

Data Number

Rater 1 Rater 2 Rater 3 Total Mean



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When the statistical calculation is finished, the data are classified into three


1. Classification A: Acceptable, includes the data with score mean 1.00

– 1.59.

2. Classification B: Less Acceptable includes the data with score mean

1.60 – 2.59.

3. Classification C: Inacceptable, includes the data with score mean 2.60

– 3.00.

Based on the table of acceptability in appendix, of 172 data, 157 data

(91.28%) were acceptable or in classification A, 15 data (8.72%) were less

acceptable or in classification B, and there was no data classified as inacceptable

or in classification C.

Mean of all data data = : total data

= : 172

= 1.20 (A)

It means that equally the acceptability level of the website is A /

Acceptable.

Table 4.2.2

The table distribution of acceptability level:

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A

002, 003, 004, 005, 006, 007, 008, 009, 010, 011, 012, 013, 014, 015, 016, 017, 018, 019, 020, 021, 022, 023, 024, 025, 026, 027, 028, 029, 030, 031, 032, 034, 035, 036, 037, 038, 039, 040, 043, 045, 046, 047, 048, 049, 050, 051, 052, 053, 054, 055, 056, 057, 058, 060, 061, 063, 064, 065, 066, 067, 068, 069, 070, 071, 072, 073, 074, 075, 076, 077, 078, 079, 080, 081, 082, 083, 084, 085, 086, 087, 088, 089, 090, 091, 092, 093, 094, 095, 096, 097, 099, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 136, 137, 138, 141, 142, 143, 144, 145, 146, 147, 148, 149, 151, 153, 155, 156, 157, 158, 159, 160, 161, 163, 164, 165, 167, 168, 169, 170, 171, 172

157

B 033, 040, 041, 052, 074, 098, 123, 134, 135, 139, 140, 150, 152, 154, 162 15

C 0 0

Total 172

1. Classification A: Acceptable Translation.

All data classified in this classification are acceptable. The mean score of

the data is from 1.00 – 1.59. There are 157 data (91.28%), considered to be

acceptable. They are classified as acceptable translation since they sound natural

and appropriate with the TL grammar, and do not feel like translation.


Example 1:

061. My friends

061. Teman saya

Example 2:

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068. Personal Information

068. Informasi pribadi

Example 3:

116. Activity Partners

116. Mitra aktivitas

Those three examples are phrases that are considered to be acceptable. All

of three raters gave point 1.00 for those three examples. All of those examples

apply structure shift from H – M into M - H that make the translation of those

phrases become acceptable.

All of three raters agree that those sentences are acceptable. They gave

score 1.00 for each phrase, and make the mean score become 1.00 that is

acceptable according to the scale of acceptability.

2. Classification B: Less Acceptable Translation.

All data classified in this classification are acceptable. The mean score of

the data is from 1.60 – 2.59. There are 15 data (8.72%). The data are considered

less acceptable, if the translation sounds natural and appropriate with the grammar

structure of the target texts, almost does not feel like translation.


Example 1:

048. ias’s blogs

048. blog dari ias

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Different judgment was given toward this translation. Three raters gave

different opinion about the score of acceptability of this translation. Both rater 1

and 2 gave score 2, while the rater 3 gave score 1. The judgment result for this

translation is 1.66 for the mean of translation. Rater 3 argued that the translation

sounds natural and appropriate with the grammar structure of the target texts, it

almost does not feel like translation. Different opinion proposed by rater 1 and

rater 2. According to both the rater 1 and 2, the acceptability level of this

translation is not acceptable. Both rater 1 and rater 2 argued that translated phrase

sounds like translation. There is some displeasing in terms of the structure of

phrase in the target text, but almost sounds like natural. Rater 1 and rater 2 argued

that the translation of the phrase should be “blog ias”, the translator should delete

the word “dari’ in order to make the translation sounds natural for the users in

TL.

Example 2:

098. Bookmark Updates

098. Pembaruan Bookmark

There was different judgment given toward this translation. Three raters

gave different opinion about the score of acceptability of this translation. Both

rater 1 and 3 gave score 2, while the rater 2 gave score 1. The judgment result for

this translation is 1.66 for the mean of translation. According to rater 1 and 3, the

acceptability level of this translation is less acceptable. Three raters argued that

the translated phrase sounds like translation. There is some displeasing in terms of

the structure of phrase in the target text, but almost sounds like natural. Rater 2

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argued that that the translation of the phrase is acceptable because it sounds

sounds natural for the users in TL.

Example 3:

123. ºLâmβânKº's Friends

123. teman dari LamBank

Different judgment was given toward this translation. Three raters gave

different opinion about the score of acceptability of this translation. Rater 1 and

rater 2 gave score 2, while the rater 3 gave score 1. The judgment result for this

translation is 1.66 for the mean of translation. According to both the rater 1 and 2,

the acceptability level of this translation is less acceptable. Both rater 1 and rater 2

argued that translated phrase sounds like translation. There is some displeasing in

terms of the diction of the phrase in the target text, but almost sounds like natural.

According to the rater 2, argued the translation of the phrase should be “teman

LâmβânK's””. The researcher, then, agree with the opinion of rater 3. The

translation of the phrase is acceptable and it sounds natural for the users in the TL.

2.3 Readability

This section presents the analysis of the readability level of the translation

of the website of friendster.com.

The researcher involves eighteen respondents that willing to asses the

readability of text. The eighteen respondents were asked to complete the

questionnaires to determine the readability level of the translation. The

questionnaires are in form of close questionnaire. In this form of questionnaires,

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respondents determine the readability of the translation by giving mark to the

translation.

The accuracy of message transfer of the translation is measured based on

the following scale:

Scale Description

1 Easy to understand, the translation text can be understood after being

read in the first time.

2 Less easy to understand, the translation text can be understood after

being read two or three times.

3 Difficult to understand, the translation text can be understood after

being read in several times.

4 Very difficult to understand, the translation text can not be

understood at all.

After all of the questionnaires are completed by the respondents, the

researcher makes statistical calculation to determine the mean of each datum with

a formula.

Data Number

Respondent 1

….. ….. Respondent 18

Total Mean

01 score score score score total Total score Total respondents

358 score score score score total Total score Total respondents

When the statistical calculation is finished, the data are classified into four


1. Classification A: Readable, includes the data with score mean 1.00.

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2. Classification B: Less Readable includes the data with score mean

1.01 – 2.00.

3. Classification C: Unreadable, includes the data with score mean

2.01 – 3.99.

4. Classification D: Very Unreadable includes the data with score

mean 4.00.

Based on the table of readability in appendix, of 172 data, 5 data (2.91%)

were readable or in classification A, 101 data (58.72%) were less readable or in

classification B, and 66 data (38.37%) were unreadable or in classification C, and

there was no very inaccurate datum.

Table 4.2.3

The table distribution of readability level:


A 007, 010, 011, 012, 020 5

B

001, 002, 003, 004, 005, 008, 009, 013, 014, 015, 018, 019, 021, 023, 025, 026, 030, 033, 036, 038, 043, 044, 045, 046, 047, 048, 051, 053, 054, 055, 057, 058, 059, 061, 062, 063, 064, 065, 068, 069, 070, 072, 073, 075, 076, 077, 079, 081, 083, 084, 086, 087, 089, 090, 092, 095, 096, 101, 103, 108, 109, 111, 112, 113, 114, 117, 122, 124, 125, 127, 128, 129, 130, 131, 132, 133, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 157, 158, 159, 161, 164, 165, 167, 168, 169, 170, 172

101

C

006, 016, 017, 022, 024, 025, 027, 029, 031, 032, 034, 035, 037, 039, 040, 041, 042, 050, 052, 056, 060, 066, 067, 071, 074, 078, 080, 082, 085, 088, 091, 093, 094, 097, 098, 099, 100, 102, 104, 105, 106, 107, 110, 115, 116,

66

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118, 119, 120, 121, 123, 126, 134, 135, 148, 149, 150, 151, 152, 153, 154, 155, 156, 160, 162, 163, 171

D 0 0

Total 213

Mean of all data = : total data

= : 172

= 1.83 (B)

It means that equally the acceptability level of the website is B / Less

Readable.

1. Classification A: Readable Translation.

All data classified in this classification are readable. The mean score of the

data is 1.00. There are 5 data (2.91%) considered readable. The data if the

translation text can be understood after being read in the first time. The data are

classified as readable translation since the readers can understand them after being

read once.


Example 1:

010. First name.

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010. Nama depan.

Example 2:

012. Date of birth.

012. Tanggal lahir.

Example 3:

020. NEW Messages.

020. Pesan BARU.

Those three examples are classified as readable translation. All of

respondents gave score 1.00 to those examples. Example 1 is datum number 010.

It applies the transposition from H – M into M – H technique. It has the same

technique with datum number 020. Both phrases are readable according to the

respondents because the meaning in the TL can be understood after being read one

time. The example 2 is datum number 012, it applies literal translation by

translating the phrases word-for-word, but it is readable according to the

respondents because they are familiar with the translation of the phrase.

2. Classification B: Less Readable Translation.

All data classified in this classification are less readable. The mean score

of the data is in the range from 1.01 – 2.00. There are 101 data (58.72%). The data

are classified less readable since translation can be understood after being read

twice.


Example 1:

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024. NEW App Invitations

024. Undangan Aplikasi BARU

Different judgment was given toward this translation. This example is

datum number 024. The eighteen respondents had different opinion about the

readability level of this sentence. There are two respondents who gave score 4,

three respondents who gave score 3, three respondents who gave score 2, and ten

respondents gave score 1. The reader is confusing with the definition of ‘app

invitations’. They need to open the website in order to know the actual definition

of ‘app invitations’ itself. It means that the acceptability level of the phrase is

less acceptable

Example 2:

075. Manually Accept Request

075. Terima Permintaan Secara Manual



readability level of this sentence. There are one respondent who gave score 4, four

respondents who gave score 3, six respondents who gave score 2, and seven

respondents who gave score 1. The reader is confusing with the definition of

‘request’. They need to open the website in order to know the actual definition of

‘request’ itself. It means that the acceptability level of the phrase is less

acceptable.

Example 3:

140. Dating Women

140. Wanita Berkencan

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readability level of this sentence. There are one respondent gave score 4, five

respondents gave score 3, five respondents gave score 2, and seven respondents

gave score 1. The judgment result for this translation is 2.00 for the mean of

translation. There is inappropriate diction that makes the translation less readable.

The respondents argue that they could understand the phrase after reading twice,

and what makes them difficult to understand the phrase is the word of

“berkencan”. The researcher, then, argues that the translation of the word

‘dating’ should be “sedang berkencan”.

3. Classification C: Unreadable Translation.

All data classified in this classification are unreadable. The mean score of

the data is in the range from 2.01 – 3.99. There are 66 data (38.37%). The data are

classified unreadable since the translation can be understood after being read

several times.


Example 1:

093. two degrees

093. dua gelar



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readability level of this sentence. Two respondents gave score 4, six respondents

gave score 3, five respondents gave score 2, and five respondents gave score

1.The judgment result for this translation is 2.27 for the mean of translation. There

is inappropriate diction that is used by the translator in this phrase. The translator

does not translate the word ‘degrees’ into the correct translation. The translator

should translate ‘degrees’ into “tingkat”.

Example 2:

094. Email Notifications

094. Pemberitahuan Email.


datum number 094. The respondents had different opinion about the readability

level of this sentence. Two respondent gave score 4, five respondents gave score

3, four respondents gave score 2, seven respondents gave score 1. The mean score

for this translation is 2.27. The respondents are difficult to understand the

meaning of the translation phrase because there is a word that still unfamiliar for

the respondents.

Example 3:

119. Your URL

119. URL Anda


datum number 119. Four respondents gave score 4, seven respondents gave score

3, six respondents gave score 2, and 1 respondent gave score 1. The mean score

for this translation is 2.77. The respondents are difficult to understand the

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meaning of the translation phrase because there is a word that still unfamiliar for

the respondents. Even, after accessing the website they still need more time to

understand what actually the definition of the ‘URL’.

C. DISCUSION

This section presents the discussion about the result of the analysis about

the translation techniques, the accuracy level, the acceptability level, and the

readability level of the translation of the website of friendster.com.

The result of the analysis of this research is summarized in the following

table:

Table 4.2.4

The Techniques and the Level of Accuracy, Acceptability, and Readability

Translation Techniques

Translation Quality Assessments Number of Data

Percentage

Accurate 5 71.43 %

Less Accurate 2 28.57 %

Inaccurate 0 0 % Accuracy

Very Inaccurate 0 0 %

Acceptable 7 100 %

Less Acceptable 0 0 % Acceptability

Inacceptable 0 0%

Readable 0 0 %

Less Readable 6 85.71 %

Addition (7 data)

Readability

Unreadable 1 14.29 %

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Very Unreadable 0 0 %

Accurate 21 100 %

Less Accurate 0 0 %



Acceptable 20 95.24 %

Less Acceptable 1 4.76 % Acceptability

Inacceptable 0 0 %

Readable 1 4.77 %


Unreadable 8 38.09%

Borrowing (21 data)

Readability


Accurate 30 90.90 %






Inacceptable 0 0 %

Readable 0 0 %



Naturalization (33 data)

Readability


Accurate 32 94.12 %






Inacceptable 0 0 %

Literal Translation (34 data)

Readability Readable 1 1.78 %

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Accurate 8 80 %

Less Accurate 2 20 %



Acceptable 10 100 %

Less Acceptable 0 0 % Acceptability

Inacceptable 0 0 %

Readable 0 0 %

Less Readable 5 50 %

Unreadable 5 50 %

Free Translation (10 data)

Readability


Accurate 31 88.57 %






Inacceptable 0 0 %

Readable 1 2.85 %



Structure Shift From Plural into Singular

(35 data)

Readability


Accurate 117 88.12 %





Structure Shift From Head – Modifier into

Modifier – Head

(138 data) Acceptability

Less Acceptable 10 7.25 %

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Inacceptable 0 0 %

Readable 3 1.45 %


Unreadable 52 37.68 % Readability


Accurate 10 90.90 %






Inacceptable 0 0 %

Readable 0 0 %



Unit Shift from Word into

Phrase (11 data)

Readability


The result of data analysis shows that the data are classified into 8

categories based on the translation techniques involved. The technique that is

most frequently used is structure shift from (M-H) into (H-M). There are 138 data

or 47.59% from the overall data. Among 138 data, 117 data are considered to be

accurate translation, 21 data are considered to be less accurate translation. There

are 128 data are considered to be acceptable translation, 10 data are considered to

be less acceptable translation, among 138 data, 3 data are considered to be

readable translation, 84 data are considered to be less readable translation, and 52

data are considered as unreadable translation. In other words, majority of the data

translated by using structure shift from (M-H) into (H-M) tend to be accurate,

acceptable, but less readable.

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The following technique is structure shift from plural into singular. There

are 35 data identified as this translation technique or 12.07% from total the overall

data. Among 35 data, 31 data are considered to be accurate translation, 4 data are

considered to be less accurate translation. There are 31 data are considered to be

acceptable translation, 4 data are considered to be less acceptable translation. In

addition, among 35 data, 1 datum is considered to be readable translation, 22 data

are considered to be less readable translation, and 12 data are considered as

unreadable translation. In other words, majority of the data translated by using

structure shift from plural into singular tend to be accurate, acceptable, but less

readable.

The following technique is literal translation. There are 34 data or 11..72%

from the overall data. Among 34 data, 32 data are considered to be accurate

translation, 2 data are considered to be less accurate translation. There are 30 data

considered to be acceptable translation, 4 data are considered to be less acceptable

translation. In addition, among 34 data, 1 datum is considered to be readable

translation, 24 data are considered to be less readable translation, and 9 data are

considered as unreadable translation. In other words, majority of the data

translated by using literal translation technique tend to be accurate, acceptable, but

less readable.

The next classification is naturalization. There are 33 data classified in this

category or 11.38% from the overall data. Among 33 data, 30 data are considered

to be accurate translation, 3 data are considered to be less accurate translation.

There are 31 data are considered to be acceptable translation, 2 data are

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considered to be less acceptable translation. In addition, among 33 data, 18 data

are considered to be less readable translation, and 15 data are considered as

unreadable translation. In other words, majority of the data translated by using

naturalization technique tend to be accurate, acceptable, but less readable.

The next category is borrowing or borrowing plus explanation with 21 data

include in this category or 7.24% from total of translation technique used. Among

21 data, 21 data are considered to be accurate translation. There are 20 data are

considered to be acceptable translation, 1 datum is considered to be less

acceptable translation. In addition, among 21 data, 1 datum is considered to be

readable translation, 12 data are considered to be less readable translation, and 8

data are considered as unreadable translation. In other words, majority of the data

translated by using borrowing or borrowing plus explanation technique tend to be

accurate, acceptable, but less readable.

The next category is unit shift from word into phrase with 11 data or

3.79% from the overall data. Among 11 data, 10 data are considered to be

accurate translation, 1 datum is considered to be less accurate translation. There

are 9 data are considered to be acceptable translation and 2 data are considered to

be less acceptable. In addition, among 11 data, 8 data is considered to be less

readable translation, 3 data are considered to be unreadable translation. In other

words, majority of the data translated by using addition technique tend to be

accurate, acceptable, but less readable.

The further technique used in translation of the friendster website is free

translation with 10 data or 3.45% from the overall data. Among 10 data, 8 data are

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considered to be accurate translation and 2 datum are considered to be less

accurate. There are 10 data are considered to be acceptable translation. In

addition, among 10 data, 5 datum are considered to be less readable translation, 5

datum are considered to be unreadable translation. In other words, majority of the

data translated by using addition translation technique tend to be accurate,

acceptable.

The last category is addition 7 data or 2.76% from the overall data. Among

7 data, 5 datum is considered to be accurate translation, 2 data are considered to

be less accurate translation. There are 7 data are considered to be acceptable

translation. In addition, among 7 data, 6 data are considered to be less readable

translation, 1 datum is considered to be unreadable translation. In other words,

majority of the data translated by using unit shift from word into phrase technique

tend to be accurate, acceptable.

ACCURACY

From the analysis of the questionnaire spread to three raters, the researcher

found out that most of the translations are accurate with 172 data. In this case,

accurate translation is the data that the average point range 1.00. The most

frequent score given to the data is 1.00. The correct transfer of the content of the

source text defines the accuracy of the translation importantly. In addition to be

considered accurate, a translated text must be clearly understood and does not

need any rewriting.

lxxvi

Although most of the data are included in accurate translation, it cannot be

inferred that the translation of the website is good quality. The reason is that there

are 26 data that are less accurate if it is seen from the transfer of the source text

content. Each rater has their own consideration in giving scores to each of the

data, but the researcher has set the scoring system to rate the accuracy level of the

translation. Thus, the average score given by the raters can be used as a pointer for

the accuracy level. Moreover, the raters are all experienced in translation theory,

practice, and having competence in both English and Indonesian language. In

general, the accuracy level translation of the friendster website is accurate.

ACCEPTABILITY

From the analysis of the questionnaire spread to three raters, the researcher

found out that most of the translations are acceptable with 172 data. The

acceptability of the translation is defined importantly by the natural sounds of

translation and appropriate translation with the grammar structure of the target

texts. In addition to be considered acceptable, a translated text must sound natural

and appropriate with the grammar structure of the target texts.

Although most of the data are included in acceptable translation, it cannot

be inferred that the translation of the website is high quality. The reason is

because there are 15 data that are less acceptable if it is seen from the transfer of

the source text content. Each rater has their own consideration in giving scores to

each of the data, but the researcher has set the scoring system to rate the

acceptability level of the translation. Thus, the average score given by the raters

lxxvii

can be used as a pointer for the accuracy level. Moreover, the raters are all

experienced in translation theory and practice and having competence in both

English and Indonesian language. In general, the acceptability level of translation

of the friendster website is acceptable.

READABILITY

The readability of the translation is defined importantly by the

understandability of texts to the target text users. In addition to be considered

readable, a translated text must be understood after being read only 1 time. From

the analysis of the questionnaire spread to 18 respondents, the researcher found

out that most of the translations are less readable with 101 data. In this case,

readability translation is the data that the average point range 1.01 – 2.00.

There are 66 data that are unreadable. Moreover, although in the smallest

number, there is only 5 data that is classified as readable translation. Each

respondent has their own consideration in giving scores to each data based on

their ability in understanding the data, and the researcher has set the scoring

system to rate the readability level of the translation. Thus, the average score

given by the respondents can be used as a pointer for the accuracy level. In

general, the readability level of translation of the friendster website is less

readable.

lxxviii

CHAPTER V

CONCLUSION AND RECOMMENDATION

A. Conclusion

After the data analysis has been completed, the researcher draws some

conclusions based on the problem statements and the results of the data analysis.

The conclusions are as follows:

1. The translation techniques used by the translator in translating the

phrases of friendster.com are structure shift from (M-H) into (H-M) (138 data or

47.59%), structure shift from plural into singular (35 data or 12.07%), literal

translation (34 data or 11.72%), naturalization (33 data or 11.38%), borrowing or

borrowing plus explanation (21 data or 7.24%), unit shift from word into phrase

(11 data or 3.79%) free translation (10 data or 23.45%), and addition (74 data or

2.76%).

2. The analysis on translation accuracy shows that there are 146 data

(84.88%) considered to be accurate translation with classification A. There 26

data (15.12%) considered to be less accurate with classification B. The techniques

result in high level of accuracy is structure shift from (M-H) into (H-M) with 117

data. The techniques result in low level of accuracy is addition with 5 data.

The analysis on translation acceptability shows that there are 157 data

(91.28%) considered to be acceptable translation with classification A. There are

15 data (8.72%) considered to be less acceptable with classification B. The

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techniques results in high level of acceptability are structure shift from (M-H) into

(H-M) with 128 data. The technique result in low level of acceptability is unit

shift from word into phrase with 9 data.

The analysis on translation readability shows that there are 5 data (2.91%)

considered to be readable translation with classification A. There are 101 data

(58.72%) considered to be less readable with classification B. There are 66 data

(38.37%) considered to be unreadable translation with classification C. The

technique result in high level of readability is structure shift from Head – Modifier

into Modifier – Head with 3 data. The techniques results in low level of

readability are addition, naturalization, free translation, and unit shift from word

into phrase with 0 data.

B. Recommendation

Regarding the result of the research, the researcher suggests several

recommendations to:

1. English Department Students

The researcher expects that the result of the research could be

advantageous as one of the informational source to enlarge and sharpen

knowledge for the English department students, especially for those who

are studying translation of the translation, as an additional input and

reference to enlarge their knowledge of translation especially translation of

website.

lxxx

2. The Friendster.com Translator

The translator of the friendster.com should be aware that there are always

differences of the source language and the target language, grammatically,

either semantically, or stylistically. Therefore, the translator should be able

to choose and apply the proper technique to produce a good translation for

the improvement of the website quality.

3. Other Researchers

The result of this study could be used as a reference by other researchers to

conduct a further research related to the website translation quality

assessment.

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BIBLIOGRAPHY

Baker, Mona. 1992. In Other Words: A Coursebook on Translation. London: Sage

Publication.

Bell, Roger.T. 1991. Translation and Translating: theory and Practice. London:

Longman.

Catford, J. 1965. Linguistic Theory of Translation. Oxford: Oxford University

Press.

Creswell, John W. 1998. Qualitative Inquiry and Research Design: Choosing

among Five Traditions. California: Sage Publications.

Cyrus, Lea. 2006. Building a Resource for Studying Translation Shifts. Germany:

Arbeitsbereich Linguistik, University of M¨unster.

Fraenkel, Jack R. and Norman E. Wallen. 2000. How to Design and evaluate

Research in Education. New York: McGraw-Hill Company.

Finlay, Ian F. 1971. Teach Translation: Book Translation. Edinburgh: T and A

Lonstable Ltd.

Hadi, Sutrisno. 1989. Methodology Research. Yogyakarta: Yayasan Penerbitan

Fak. Psikologi UGM

Larson, Mildred. 1984. Meaning-Based Translation: a Guide to Cross Language

Equivalence. Lanham: University Press of America.

Machali, Rochayah. 2000. Pedoman bagi Penerjemah. Jakarta: Grasindo.

Nababan, M. Rudolf. 2003. Teori Menerjemahkan Bahasa Inggris. Yogyakarta:

Pustaka Pelajar

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Nababan, M. Rudolf. 2004. Strategi Penilaian Kualitas Terjemahan Dalam Jurnal

Linguistik Bahasa Volume 2 No.1 Halaman 54-56. Fakulas Sastra dan

Seni Rupa. Universitas Sebelas Maret: Surakarta. Mei 2004

Newmark, Peter. 1988. A Textbook of Translation. Oxford: Pergamon Press

Nida, Eugine A and Charles R. Tabert. 1974. The Theory and Preactice of

Translation. Leiden: E. J Brill

Nida, Eugine A. 1964. Toward A Science of Translatin. Leisen: E. J Brill

Shuttleworth and Cowie. 1997. Dictionary of Translation Studies. Manchester: St

Edmundbury Press Ltd.

Sofyan, Ahmad. 2003. Kesepadanan dalam Penerjemahan. Semarang:

Universitas Negeri Semarang.

Suryawinata dan Hariyanto.2000. Translation: Bahasan Teori & Penuntun

Praktis Menerjemahkan. Malang: Kanisius.

www.friendster.com Due date: December 23, 2009 at 12:26 pm www.webupon.com/Social-Networks/The-History-of-Friendster.102940 Due date: January 12, 2009 at 9:51 am

www.erudit.org/revue/meta/2000/v45/n3/001878ar.pdf www.emanueltov.info/docs/papers/16.trans.techn.1999.pdf www.sportsci.org/jour/0001/wghdesign.htm www.southalabama.edu/coe/bset/johnson/lectures/lec14.htm http://ezinearticles.com/?Culture-and-Website-Localization&id=832 Due date: January 12, 2009 at 10:03 am www.geocities.com

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