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1.1. Uji Normalitas a. Grafik Histogram
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b. Grafik Normal Plot
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c. Hasil Uji Normalitas dengan Uji Kolmogorov-Smirov
One-Sample Kolmogorov-Smirnov Test
Unstandardized Residual N
68 Normal Parameters
a,,b
Mean .0000000
Std. Deviation .37143364
Most Extreme Differences Absolute
.129 Positive
.116 Negative
-.129 Kolmogorov-Smirnov Z
1.065 Asymp. Sig. 2-tailed
.207 a. Test distribution is Normal.
b. Calculated from data.
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1.2 Uji Heteroskedastisitas a. Grafik Scatterplot
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b. Uji Glejser
Model Unstandardized Coefficients
Standardized Coefficients
t Sig.
B Std. Error
Beta 1
Constant .448
.519 .864
.391 BOPO
-.003 .005
-.072 -.544
.588 NPL
-.007 .040
-.025 -.187
.852 CAR
.008 .010
.110 .832
.409 LDR
-.003 .003
-.117 -.850
.399 NIM
.016 .027
.083 .588
.559 a. Dependent Variable: ABS_RES
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1.3. Uji Autokorelasi a. Uji Runs
b. Uji Durbin-Watson
Model Summary
b
Model R
R Square Adjusted R
Square Std. Error of the
Estimate Durbin-Watson
1 .889
a
.790 .773
.38612 2.062
a. Predictors: Constant, NIM, CAR, NPL, BOPO, LDR b. Dependent Variable: ROA
Hasil Uji Runs
Unstandardized Residual
Test Value
a
-.00236 Cases Test Value
34 Cases = Test Value
34 Total Cases
68 Number of Runs
37 Z
.489 Asymp. Sig. 2-tailed
.625 a. Median
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1.4. Uji Multikolinieritas
Coefficients
a
Model Unstandardized
Coefficients Standardized
Coefficients t
Sig. Collinearity
Statistics B
Std. Error Beta
Tolerance VIF
1 Constant
8.267 .706
11.710 .000
BOPO -.084
.007 -.804 -12.895
.000 .870
1.150 NPL
-.017 .054
-.019 -.307
.760 .896
1.116 CAR
-.009 .014
-.040 -.650
.518 .879
1.137 LDR
.001 .004
.023 .362
.719 .807
1.240 NIM
.115 .036
.210 3.161
.002 .769
1.300 a. Dependent Variable: ROA
2. Pengujian Hipotesis
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2.1. Analisis Regresi Berganda