Hasil Analisis Data - 26 Nov 2014

Descriptives

Descriptive Statistics

N Minimum Maximum Mean Std. Deviation

Sales Growth 57 .00 .89 .4019 .18205

Profitabilitas 57 .10 .89 .4312 .18984

Likuiditas 57 .00 .80 .4023 .17792

Struktur Aktiva 57 .10 .81 .4253 .17310

Struktur Modal 57 -.22 .82 .2800 .25715

Valid N (listwise) 57

NORMALITAS

Explore

Case Processing Summary

Cases

Valid Missing Total

N Percent N Percent N Percent

Sales Growth 57 100.0% 0 .0% 57 100.0%

Profitabilitas 57 100.0% 0 .0% 57 100.0%

Likuiditas 57 100.0% 0 .0% 57 100.0%

Struktur Aktiva 57 100.0% 0 .0% 57 100.0%

Struktur Modal 57 100.0% 0 .0% 57 100.0%

Descriptives

Statistic Std. Error

Sales Growth Mean .4019 .02411

95% Confidence Interval for Mean

Lower Bound .3536

Upper Bound .4502

5% Trimmed Mean .3991

Median .3600

Variance .033

Std. Deviation .18205

Minimum .00

Maximum .89

Range .89

Interquartile Range .25

Skewness .294 .316

Kurtosis .300 .623

Profitabilitas Mean .4312 .02515

Lower Bound .3809


Upper Bound.4816


Median .4300

Variance .036


Minimum .10

Maximum .89

Range .79


Skewness .591 .316

Kurtosis -.068 .623

Likuiditas Mean .4023 .02357


Lower Bound .3551

Upper Bound .4495


Median .3600

Variance .032


Minimum .00

Maximum .80

Range .80


Skewness .151 .316

Kurtosis -.012 .623

Struktur Aktiva Mean .4253 .02293


Lower Bound .3793

Upper Bound .4712


Median .4000

Variance .030


Minimum .10

Maximum .81

Range .71


Skewness .347 .316

Kurtosis -.447 .623

Struktur Modal Mean .2800 .03406


Lower Bound .2118

Upper Bound .3482


Median .2700

Variance .066


Minimum -.22

Maximum .82

Range 1.04


Skewness -.051 .316

Kurtosis -.572 .623

Tests of Normality

Kolmogorov-Smirnova Shapiro-Wilk

Statistic df Sig. Statistic df Sig.

Sales Growth .100 57 .200* .975 57 .286

Profitabilitas .110 57 .086 .961 57 .064

Likuiditas .103 57 .200* .972 57 .219

Struktur Aktiva .112 57 .070 .966 57 .115

Struktur Modal .074 57 .200* .980 57 .479

a. Lilliefors Significance Correction

*. This is a lower bound of the true significance.

Tes Kolmogorov Smirnov memakai criteria pengujian sebagai berikut :- Signifikansi > 0,05, maka data berdistribusi normal- Signifikansi < 0,05, maka data tidak berdistribusi secara normal

Dari hasil tests of normality di atas dapat dilihat signifikansi X1, X2, X3, X4 dan Y lebih dari 0,05, maka dapat dikatakan data berdistribusi secara normal. Hal ini dapat dilihat pada gambar Normal Q.Q Plot …..

Charts

NPar Tests

One-Sample Kolmogorov-Smirnov Test

Mean

N 57

Normal Parametersa Mean .2800


Most Extreme Differences Absolute .074

Positive .055

Negative -.074

Kolmogorov-Smirnov Z .556

Asymp. Sig. (2-tailed) .917

a. Test distribution is Normal.

ANALISIS REGRESI LINIER BERGANDA

Regression

Variables Entered/Removedb

ModelVariables Entered

Variables Removed Method

1 Struktur Aktiva, Likuiditas, Profitabilitas, Sales Growtha

. Enter

a. All requested variables entered.

b. Dependent Variable: Struktur Modal

Model Summaryb

Model R R SquareAdjusted R

SquareStd. Error of the

Estimate Durbin-Watson

1 .469a .220 .160 .23574 1.846

a. Predictors: (Constant), Struktur Aktiva, Likuiditas, Profitabilitas, Sales Growth


ANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression .813 4 .203 3.658 .011a

Residual 2.890 52 .056

Total 3.703 56



Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t Sig.

Collinearity Statistics

BStd. Error Beta Tolerance VIF

1 (Constant) .040 .094 .422 .675

Sales Growth

-.349 .271 -.247 -1.289 .203 .409 2.446

Profitabilitas .340 .245 .251 1.389 .171 .459 2.179

Likuiditas .640 .255 .443 2.509 .015 .482 2.074

Struktur Aktiva

-.055 .250 -.037 -.220 .827 .528 1.893

a. Dependent Variable: Struktur Modal

Collinearity Diagnosticsa

Model Dimension EigenvalueCondition

Index

Variance Proportions

(Constant)Sales

Growth Profitabilitas LikuiditasStruktur Aktiva

1 1 4.719 1.000 .00 .00 .00 .00 .00

2 .100 6.873 .70 .09 .03 .12 .03

3 .079 7.710 .19 .00 .05 .36 .41

4 .060 8.857 .00 .42 .73 .00 .04

5 .041 10.674 .11 .48 .19 .51 .52


Casewise Diagnosticsa

Case Number Std. Residual Struktur Modal Predicted Value Residual

1 -1.520 -.04 .3183 -.35829

2 .742 .31 .1350 .17502

3 -.550 .12 .2497 -.12966

4 -2.640 -.17 .4525 -.62247

5 -.857 .14 .3421 -.20212

6 -.562 .25 .3826 -.13259

7 -.720 .06 .2297 -.16968

8 -.706 .00 .1664 -.16636

9 -2.178 -.22 .2934 -.51338

10 -1.407 .04 .3718 -.33180

11 -.240 .15 .2065 -.05649

12 -1.574 -.15 .2212 -.37115

13 -1.964 -.11 .3530 -.46301

14 -1.266 -.12 .1786 -.29856

15 -.737 .04 .2137 -.17371

16 -.055 .24 .2530 -.01302

17 -2.253 -.19 .3412 -.53121

18 -1.045 .00 .2465 -.24647

19 -1.058 -.07 .1795 -.24947

20 1.123 .60 .3353 .26465

21 .009 .15 .1478 .00217

22 .358 .36 .2756 .08439

23 1.343 .82 .5035 .31654

24 .788 .50 .3143 .18569

25 .331 .54 .4619 .07814

26 .339 .35 .2701 .07985

27 .135 .20 .1683 .03173

28 .498 .39 .2727 .11733

29 .844 .58 .3811 .19889

30 -.014 .27 .2732 -.00322

31 .529 .32 .1953 .12472

32 .964 .50 .2728 .22718

33 .335 .27 .1911 .07888

34 -.068 .73 .7460 -.01600

35 .902 .41 .1973 .21272

36 1.671 .66 .2662 .39383

37 .554 .38 .2494 .13062

38 .312 .26 .1864 .07362

39 .776 .51 .3270 .18299

40 .187 .14 .0959 .04413

41 .515 .34 .2186 .12139

42 1.209 .80 .5150 .28498

43 .789 .49 .3041 .18590

44 .990 .53 .2967 .23332

45 .479 .32 .2071 .11292

46 .376 .22 .1313 .08868

47 .052 .50 .4877 .01228

48 .563 .56 .4272 .13282

49 .134 .27 .2385 .03149

50 .372 .34 .2524 .08761

51 .792 .57 .3834 .18660

52 .389 .26 .1683 .09173

53 -.123 .00 .0290 -.02901

54 .438 .33 .2267 .10325

55 .841 .58 .3818 .19819

56 .516 .36 .2383 .12171

57 .347 .27 .1883 .08174


Residuals Statisticsa

Minimum Maximum Mean Std. Deviation N

Predicted Value .0290 .7460 .2800 .12050 57

Std. Predicted Value -2.083 3.867 .000 1.000 57

Standard Error of Predicted Value

.034 .191 .061 .035 57

Adjusted Predicted Value .0849 .7732 .2835 .12396 57

Residual -.62247 .39383 .00000 .22717 57

Std. Residual -2.640 1.671 .000 .964 57

Stud. Residual -2.872 1.716 -.006 1.003 57

Deleted Residual -.73624 .41532 -.00355 .24781 57

Stud. Deleted Residual -3.100 1.749 -.015 1.028 57

Mahal. Distance .190 35.876 3.930 7.425 57

Cook's Distance .000 .301 .019 .052 57

Centered Leverage Value .003 .641 .070 .133 57


AUTOKORELASI

Model Summaryb

Model R R SquareAdjusted R

SquareStd. Error of the

Estimate Durbin-Watson

1 .469a .220 .160 .23574 1.846



Prasyarat yang harus terpenuhi adalah tidak adanya autokorelasi dalam model regresi. Metode pengujian yang sering digunakan adalah dengan Uji Durbin Watson (Uji DW) dengan ketentuan sebagai berikut :1. Jika d lebih kecil dari dL atau lebih besar dari (4-dL) maka hipotesis nol ditolak, yang

berarti terdapat autokorelasi.2. Jika d terletak antara dU dan (4-dU) maka hipotesis nol diterima, yang berarti tidak

terdapat autokorelasi.3. Jika d terletak antara dL dan dU atau di antara (4-dU) dan (4-dL), maka tidak

menghasilkan kesimpulan yang pasti.

Dari hasil output di atas didapat nilai DW = 1,846. Berdasarkan Tabel DW dengan signifikansi 0,05 dan jumlah data (n) = 57, serta k = 4 (jumlah variabel) diperoleh nilai :dL = 1,285dU = 1,721Karena nilai DW pada penelitian ini berada antara dU dan (4-dU) maka hipotesis nol diterima, yang berarti tidak terdapat autokorelasi

Hasil Analisis Data - 26 Nov 2014

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