129
X2 = SR = α∑xy JKreg x 100 = 3.504.337,21 4.089.227,21 x 100
= 0,856968 x 100 = 85,7
Sumbangan Efektif SE
X1 = SE = SR x R
2
= 14,3 x 0,809 = 11,6
X2 = SE = SR x R
2
= 85,7 x 0,809 = 69,3
130
LAMPIRAN 7. HASIL ANALISIS DATA DAN UJI HIPOTESIS 1.
UJI REGRESI SEDERHANA AKUNTABILITAS
Variables EnteredRemoved
b
Model Variables
Entered Variables
Removed Method
1 A
a
. Enter a. All requested variables entered.
b. Dependent Variable: KAT
Model Summary
Model R
R Square Adjusted R
Square Std. Error of the
Estimate 1
.378
a
.143 .129
4.505 a. Predictors: Constant, A
ANOVA
b
Model Sum of Squares
df Mean Square
F Sig.
1 Regression
206.883 1
206.883 10.193
.002
a
Residual 1238.101
61 20.297
Total 1444.984
62 a. Predictors: Constant, A
b. Dependent Variable: KA
Coefficients
a
Model Unstandardized Coefficients
Standardized Coefficients
t Sig.
B Std. Error
Beta 1
Constant 22.450
3.657 6.138
.000 A
.452 .142
.378 3.193
.002 a. Dependent Variable: KA
131
2. UJI REGRESI SEDERHANA INDEPENDENSI
Variables EnteredRemoved
b
Model Variables
Entered Variables
Removed Method
1 I
a
. Enter a. All requested variables entered.
b. Dependent Variable: KA
Model Summary
Model R
R Square Adjusted R
Square Std. Error of the
Estimate 1
.889
a
.790 .787
2.229 a. Predictors: Constant, I
ANOVA
b
Model Sum of Squares
df Mean Square
F Sig.
1 Regression
1141.790 1
1141.790 229.718
.000
a
Residual 303.194
61 4.970
Total 1444.984
62 a. Predictors: Constant, I
b. Dependent Variable: KA
Coefficients
a
Model Unstandardized Coefficients
Standardized Coefficients
t Sig.
B Std. Error
Beta 1
Constant 6.788
1.816 3.737
.000 I
1.064 .070
.889 15.156
.000 a. Dependent Variable: KA
132
3. UJI REGRESI LINIER BERGANDA
Variables EnteredRemoved
Model Variables Entered
Variables Removed
Method 1
IT, AT
a
. Enter a. All requested variables entered.
Model Summary
b
Model R
R Square Adjusted R
Square Std. Error of the
Estimate Change Statistics
Durbin-Watson R Square
Change F Change
df1 df2
Sig. F Change 1
.899
a
.809 .803
2.145 .809
126.988 2
60 .000
2.052 a. Predictors: Constant, IT, AT
b. Dependent Variable: KAT
133
ANOVA
b
Model Sum of Squares
df Mean Square
F Sig.
1 Regression
1168.852 2
584.426 126.988
.000
a
Residual 276.132
60 4.602
Total 1444.984
62 a. Predictors: Constant, IT, AT
b. Dependent Variable: KAT
Coefficients
a
Model Unstandardized Coefficients
Standardized Coefficients
T Sig.
Collinearity Statistics B
Std. Error Beta
Tolerance VIF
1 Constant
3.656 2.173
1.682 .098
AT .170
.070 .142
2.425 .018
.923 1.084
IT 1.016
.070 .849
14.458 .000
.923 1.084
a. Dependent Variable: KAT
134
135