86
Lampiran 9
Hasil Uji Hipotesis
1.
Regresi Linear Berganda
Model Summaryb
Model R R Square
Adjusted R Square
Std. Error of the
Estimate Durbin-Watson
1 ,890a ,791 ,789 1,077 1,985
a. Predictors: (Constant), X2, X1 b. Dependent Variable: Y
Coefficientsa
Model
Unstandardized Coefficients
Standardize d Coefficients
t Sig.
Collinearity Statistics
B Std. Error Beta Tolerance VIF
1 (Constant) ,296 ,468 ,633 ,528
X1 ,098 ,016 ,446 6,002 ,000 ,234 4,278
X2 ,215 ,034 ,473 6,373 ,000 ,234 4,278
a. Dependent Variable: Y
2.
Uji F
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression 712,725 2 356,363 307,174 ,000b
Residual 187,941 162 1,160
Total 900,667 164
a. Dependent Variable: Y b. Predictors: (Constant), X2, X1
3.
Uji t
Coefficientsa
Model
Unstandardized Coefficients
Standardize d Coefficients
t Sig.
Collinearity Statistics
B Std. Error Beta Tolerance VIF
1 (Constant) ,296 ,468 ,633 ,528
X1 ,098 ,016 ,446 6,002 ,000 ,234 4,278
X2 ,215 ,034 ,473 6,373 ,000 ,234 4,278
