LAMPIRAN 1
DATA SAMPEL DAN VARIABEL PENELITIAN
LAMPIRAN 2
DATA HASIL OUTPUT SPSS 16
CR DER ROA
RETURN
DISCRIPTIVE STATISTIC
Descriptives
Descriptive Stati stics
30 .45 1.70 .7963 .33493
30 -1.83 3.09 -.3846 .89356 30 -.12 3.22 2.3460 .74959
30 -.82 .54 .0742 .29167
30 LNCR
LNDER LNROA
RETURN SAHAM Valid N (list wise)
UJI ASUMSI KLASIK
UJI NORMALITAS
NPar Tests
One-Sample Kolmogorov-Smirnov Test
30 -.0213579 .26957201 .134 .050 -.134 .733 .656 N
Mean
Std. Dev iat ion Normal Parametersa,b
Absolute Positiv e Negativ e Most Extreme
Dif f erences
Kolmogorov -Smirnov Z Asy mp. Sig. (2-tailed)
Unstandardiz ed Residual
Test distribution is Normal. a.
UJI MULTIKOLINIERITAS
Regression
Variabl es Entered/Removedb
LNROA,
Remov ed Method
All requested v ariables entered. a.
Dependent Variable: RETURN SAHAM b.
Model Summaryb
2.317a Model
1
Durbin-W atson
Predictors: (Const ant ), LNROA, LNDER, LNCR a.
Dependent Variable: RETURN SAHAM b.
Coeffi ci entsa
.648 1.544
Tolerance VI F Collinearity Statistics
Dependent Variable: RETURN SAHAM a.
Collinearity Diagnosticsa
3.157 1.000 .01 .01 .03 .01
Index (Constant) LNCR LNDER LNROA Variance Proportions
Dependent Variable: RETURN SAHAM a.
Residual s Statisti csa
-.2618 .6431 .0742 .18305 30
-.5622 .4724 .0000 .22707 30
-1.836 3.108 .000 1.000 30
-2.344 1.970 .000 .947 30
Predicted Value Residual
Std. Predicted Value Std. Residual
Minimum Maximum Mean Std. Dev iat ion N
UJI AUTOKORELASI
Regression
Variabl es Entered/Removedb
LNROA,
Remov ed Method
All requested v ariables entered. a.
Dependent Variable: RETURN SAHAM b.
Model Summaryb
.628a .394 .324 .23982 2.317
Model
Predictors: (Constant), LNROA, LNDER, LNCR a.
Dependent Variable: RETURN SAHAM b.
ANOVAb
.972 3 .324 5.632 .004a
1.495 26 .058
2.467 29
Squares df Mean Square F Sig.
Predictors: (Constant), LNROA, LNDER, LNCR a.
Dependent Variable: RETURN SAHAM b.
Coeffi ci entsa
-.032 .151 -.213 .833
-.409 .165 -.469 -2.474 .020
.138 .053 .422 2.620 .014
.207 .073 .531 2.829 .009
(Constant)
Coef f icients
Beta St andardized Coef f icients
t Sig.
Dependent Variable: RETURN SAHAM a.
Residual s Statisti csa
-.2618 .6431 .0742 .18305 30 -.5622 .4724 .0000 .22707 30
-1.836 3.108 .000 1.000 30
-2.344 1.970 .000 .947 30
Predicted Value Residual
Std. Predicted Value Std. Residual
Minimum Maximum Mean Std. Dev iat ion N
UJI HETOSKEDASTISITAS
Regression
Variabl es Entered/Removedb
LNROA,
Remov ed Method
All requested v ariables entered. a.
Dependent Variable: ABSRES b.
Model Summary
.393a .155 .057 .17847 Model
Predictors: (Constant), LNROA, LNDER, LNCR a.
Squares df Mean Square F Sig.
Predictors: (Constant), LNROA, LNDER, LNCR a.
Dependent Variable: ABSRES b.
Coeffi ci entsa
.040 .113 .356 .724
.221 .123 .402 1.795 .084
-.008 .039 -.041 -.214 .833
-.010 .054 -.042 -.189 .851
(Constant)
Coef f icients
Beta St andardized Coef f icients
t Sig.
UJI REGRESSION
Regression
Variabl es Entered/Removedb
LNROA,
Remov ed Method
All requested v ariables entered. a.
Dependent Variable: RETURN SAHAM b.
Model Summary
.628a .394 .324 .23982 Model
Predictors: (Constant), LNROA, LNDER, LNCR a.
ANOVAb
.972 3 .324 5.632 .004a
1.495 26 .058
2.467 29
Squares df Mean Square F Sig.
Predictors: (Constant), LNROA, LNDER, LNCR a.
Dependent Variable: RETURN SAHAM b.
Coeffi ci entsa
-.032 .151 -.213 .833
-.409 .165 -.469 -2.474 .020
.138 .053 .422 2.620 .014
.207 .073 .531 2.829 .009
(Constant)
Coef f icients
Beta St andardized Coef f icients
t Sig.
