Lampiran 2 : HASIL PENGOLAHAN DATA
Descriptives
De scri ptive Statistics
80 7.82 13.95 10.1514 1.05172
80 1.00 3.00 2.3375 .69252
80 9.79 11.42 10.5871 .42228
80 25.83 31.36 28.4061 1.04236
80 4.76 8.16 6.2351 .55654
80 X1_DA U
X2_SDM X3_BL Z_KM Y_PE
Valid N (lis twis e)
N Minimum Maximum Mean St d. Deviat ion
HASIL UJI NORMALITAS NPar Tests
One-Sample Kolmogorov-Smirnov Test
80 .0000000 .31068941 .110 .094 -.110 .985 .286 N
Mean
Std. Deviation Normal Parametersa,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.
PPlot
Unstandardized Residual
Observed Cum Prob
1.0xpect
ed
C
um
P
rob
1.0
Observed Cum
Prob
1.0
evi
at
ion
N
orm
-0.05-0.10
-0.15
HASIL UJI MULTIKOLINIERITAS
Coefficientsa
.827 1.209
.875 1.143
.733 1.364
X1_DAU X2_SDM X3_BL Model
1
Tolerance VIF Collinearity Statistics
Dependent Variable: Y_PE a.
HASIL UJI AUTOKORELASI
Model Summaryb
2.112a Model
1
Durbin-Watson
Predictors: (Constant), X3_BL, X2_SDM, X1_DAU a.
Dependent Variable: Y_PE b.
HASIL UJI HETEROKEDASTISITAS
Coefficientsa
-458.623 219.393 -2.090 .040
4.114 8.104 .060 .508 .613
33.581 11.969 .324 2.806 .006
36.957 21.439 .217 1.724 .089
(Constant) X1_DAU X2_SDM X3_BL Model
1
B Std. Error Unstandardized
Coefficients
Beta Standardized
Coefficients
t Sig.
Regression
Model Summaryb
.830a .688 .676 .31676
Model 1
R R Square
Adjusted R Square
Std. Error of the Estimate
Predictors: (Constant), X3_BL, X2_SDM, X1_DAU a.
Dependent Variable: Y_PE b.
ANOV Ab
16.844 3 5.615 55.957 .000a
7.626 76 .100
24.470 79
Regres sion Residual Total Model 1
Sum of
Squares df Mean S quare F Sig.
Predic tors: (Constant), X3_B L, X2_S DM, X1_DAU a.
Dependent Variable: Y_PE b.
Coefficientsa
.469 1.009 .465 .643
.378 .037 .715 10.148 .000
.117 .055 -.146 2.131 .036
.208 .099 .158 2.110 .038
(Constant) X1_DAU X2_SDM X3_BL Model
1
B Std. Error Unstandardized
Coefficients
Beta Standardized
Coefficients
t Sig.
Dependent Variable: Y_PE a.
Residuals Statisticsa
5.2182 7.8177 6.2351 .46175 80
-1.57918 .85883 .00000 .31069 80
-2.202 3.427 .000 1.000 80
-4.985 2.711 .000 .981 80
Predicted Value Residual
Std. Predicted Value Std. Residual
Minimum Maximum Mean Std. Deviation N
Regression Standardized Residual
4 20 -2
-4 -6
Frequency
30
20
10
0
Regression Standardized Predicted Value
4 20 -2
R
egressi
on
S
tandardi
z
ed
R
esi
dual
4
2
0
-2
-4
-6
Scatterplot Dependent Variable: Y_PE
HASIL UJI MODERATED REGRESSION ANALYSIS (MRA)
Coeffi cientsa
177.199 90.283 1.963 .053
-19.934 14.423 -.155 -1. 382 .171
(Const ant) Y_PE Model
1
B St d. E rror Unstandardized
Coeffic ients
Beta St andardiz ed
Coeffic ients
t Sig.
Regression
Model Summary
.812a .660 .646 .62003
Model 1
R R Square
Adjusted R Square
Std. Error of the Estimate
Predictors: (Constant), X3_BL, X2_SDM, X1_DAU a.
ANOV Ab
56.617 3 18.872 49.092 .000a
29.217 76 .384
85.834 79
Regres sion Residual Total Model 1
Sum of
Squares df Mean S quare F Sig.
Predic tors: (Constant), X3_B L, X2_S DM, X1_DAU a.
Dependent Variable: Z_KM b.
Coefficientsa
13.084 1.974 6.627 .000
.600 .073 .606 8.231 .000
.026 .108 .017 .240 .811
.866 .193 .351 4.488 .000
(Constant) X1_DAU X2_SDM X3_BL Model
1
B Std. Error Unstandardized
Coefficients
Beta Standardized
Coefficients
t Sig.
Dependent Variable: Z_KM a.
