One-Sample Kolmogorov-Smirnov Test
104 .0000000
.33528591 .124
.122 -.124
1.259 .084
N Mean
Std. Deviation Normal Parameters
a,b
Absolute Positive
Negative Most Extreme
Differences
Kolmogorov-Smirnov Z As ymp. Sig. 2-tailed
Unstandardized Residual
Test distribution is Normal. a.
Calculated from data. b.
Estimated Distribution Parameters
.0000000 .33528591
Location Scale
Normal Dis tribution Unstandardiz
ed Res idual
The cases are unweighted.
Lampiran 13: Analisis Deskriptif Penelitian
1. Pengujian Hipotesis Pertama
A. Hasil Uji Normalitas NPar Tests Hipotesis Pertama Y
1
Descriptive Statistics
104 -.62
6.70 .6418
1.27769 104
6.22 824.16
56.1696 91.51758
104 -2.31
5.58 .9711
.72807 104
.00 3.73
.6937 .50933
104 -10.23
31.61 4.5380
5.98930 104
.01 1.15
.2445 .19582
104 VACA
VAHU STVA
MB ROA
ATO Valid N listwise
N Minimum
Maximum Mean
Std. Deviation
Observed Cum Prob
1.0 0.8
0.6 0.4
0.2 0.0
E xpect
ed C
um P
rob
1.0 0.8
0.6 0.4
0.2 0.0
Normal P-P Plot of Unstandardized Residual
Collinearity Diagnostics
a
2.409 1.000
.04 .05
.05 .05
.882 1.653
.00 .47
.36 .00
.540 2.112
.02 .38
.48 .21
.169 3.781
.94 .10
.11 .75
Di mension 1
2 3
4 Model
1 Eigenvalue
Condition Index
Constant VACA
VAHU STVA
Variance Proportions
Dependent Vari able: MB a.
Hasil Uji Autokorelasi
b
a
2.244 Model
1 Durbin-
Watson Predictors: Constant, STVA, VAHU, VACA
a. Dependent Vari able: MB
b.
B. Unstandardized Residual
C. Hasil Uji Multikolinieritas Hipotesis Pertama
D. Hasil Uji Autokorelasi Hipotesis pertama
Coefficients
a
.972 1.029
.972 1.028
.999 1.001
VACA VAHU
STVA Model
1 Tolerance
VIF Collinearity Statistics
Dependent Vari able: MB a.
Coefficients
a
1.376 .899
1.531 .000
1.241 .337
.350 3.682
.752 .004
.005 .072
.761 .449
.387 .655
.055 .592
.555 Constant
VACA VAHU
STVA Model
1 B
Std. Error Unstandardized
Coefficients Beta
Standardized Coefficients
t Sig.
Dependent Vari able: abs _res 4 a.
Variables EnteredRemoved
b
STVA, VAHU,
VACA
a
. Enter
Model 1
Variables Entered
Variables Removed
Method All requested variables entered.
a. Dependent Variable: MB
b.
Model Summary
b
.673
a
.454 .437
.34028 Model
1 R
R Square Adjusted
R Square Std. Error of
the Estimate Predictors: Constant, STVA, VAHU, VACA
a. Dependent Vari able: MB
b.
ANOV A
b
9.609 3
3.203 27.661
.000
a
11.579 100
.116 21.187
103 Regres sion
Residual Total
Model 1
Sum of Squares
df Mean S quare
F Sig.
Predic tors: Constant, STV A, V AHU, VA CA a.
Dependent Variable: M B b.
Coefficients
a
.160 .064
2.481 .015
.053 .024
-.165 2.205
.030 .000
.000 -.043
-.576 .566
.411 .047
.647 8.751
.000 Constant
VACA VAHU
SCVA Model
1 B
Std. Error Unstandardized
Coefficients Beta
Standardized Coefficients
t Sig.
Dependent Vari able: MB a.
E. Hasil Uji Heterokedastisitas Hipotesis Pertama
F. Regression
Residuals Statistics
a
-.8024 2.4506
.5077 .30543
104 -1.20734
2.07942 .00000
.33529 104
-4.289 6.361
.000 1.000
104 -3.548
6.111 .000
.985 104
Predicted Value Residual
Std. Predicted Value Std. Residual
Minimum Maximum
Mean Std. Deviati on
N
Dependent Vari able: MB a.
Regression Standardized Predicted Value
8 6
4 2
-2 -4
R egressi
on S
tandardi zed
R esi
dual
7.5 5.0
2.5 0.0
-2.5
Scatterplot Dependent Variable: MB
G. Charts
Regression Standardized Residual
7.5 5.0
2.5 0.0
-2.5
Frequency
40 30
20 10
Histogram Dependent Variable: MB
Mean =7.96E-16 Std. Dev. =0.985
N =104
One-Sample Kolmogorov-Smirnov Test
104 .0000000
2.03432614 .083
.083 -.068
.842 .478
N Mean
Std. Deviation Normal Parameters
a,b
Absolute Positive
Negative Most Extreme
Differences
Kolmogorov-Smirnov Z As ymp. Sig. 2-tailed
Unstandardized Residual
Test distribution is Normal. a.
Calculated from data. b.
Observed Cum Prob
1.0 0.8
0.6 0.4
0.2 0.0
E xpect
ed C
um P
rob
1.0 0.8
0.6 0.4
0.2 0.0
Normal P-P Plot of Unstandardized Residual
Model Summar y
b
2.030
a
Model 1
Durbin- Watson
Predictors: Constant, STVA, VAHU, VACA a.
Dependent Vari able: ROA b.
2. Pengujian Hipotesis Kedua
