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Graph 4.2 show that the spread of data which is around the diagonal line and follow the direction of the diagonal line indicates that
the regression model meets the assumption of normality.
3. Hypothesis Testing a. Multiple Regression Testing
Regression analysis is theanalys is used to measure the influence of the independent variable X on the dependent variable Y. This
method can also beused as an estimate, so it can be expected between good or bad of a variable X to reduce the level of variable Y, and
vice versa. Below is a table 4.11 of the results of multiple regression
test : Table 4.11
Multiple Regression Test
Coefficients
a
Model Unstandardized
Coefficients Standardized
Coefficients t
Sig. Collinearity Statistics
B Std. Error
Beta Tolerance
VIF
1 Constant
-10.572 10.459
-1.011 .317
KWP .603
.270 .290
2.234 .030
.814 1.229
PP .299
.134 .288
2.241 .030
.826 1.210
KP .353
.167 .259
2.120 .039
.918 1.090
a. Dependent Variable: KPP
Source: Data are processed
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Based on the results obtained from Table 4.11 above, it can be made a regression equationas follows:
From regression equation and table 4.12 shows a constant value - 10.572, t-count is -1.011 and significance value of 0.317 It states that if
the application of taxpayers consciousness, tax service and taxpayers compliance are considered constant, then the tax revenue performance
will be constant at -1.563. Regression coefficient in taxpayers consciousness is 0.603 with
significance level of 0.030, which means that ifthe variable raise the value-added, it will increase the application of taxpayers
consciousness to 0.603. Regression coefficient in tax service is 0.299 with significance
level of 0.030, which means that if the variable raise the value-added, it will increase the application of service tax authorities to 0.299.
Regression coefficient in taxpayers compliance is 0.353 with significance level of 0.039, which means that if the variable raise the
value added, it will increase the application of tax sanction to 0.353. From the three independent variables included in the regression, H
1
accepted, H
2
accepted, H
3
accepted, then the three variables had a significant influenceon the variable tax revenue performance.
Y=
-
10.572 + 0.603 X
1
+ 0.299 X
2
+ 0.353 X
3
+ e
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b. The Result of Coefficient Determination R² Table 4.12
Determination Coefficient Test R²
Model Summary
b
Model R
R Square Adjusted R
Square Std. Error of the
Estimate 1
.609
a
.371 .330
7.044 a. Predictors: Constant, KP, PP, KWP
b. Dependent Variable: KPP
Source: Data are processed The data table above shows that the 4.12 Adj R² value of 0.371
which means that only 37.1 of the dependent variable Tax Revenue Performance which may be explained by variations in the independent
variable Taxpayers consciousness, Tax Services, Taxapayers Compliance in this study. This indicates is low or weak capacity of
independent variables in explaining the dependent variable, whereas the remaining 62.9 was explained by other variables not included in
the study. The rate coefficient R indicates a value of 0.609 which indicates that the relationship between the dependent and independent
variables is quite strong because it has avalue of R 0.5. c. The Result of Statistic Fisher Test Simultaneous Test
F test aims to determine whether all the independent variables together simultaneously have a significant influenceon the dependent
variable. Significance of ther egression model tested in this study by
73
looking at the value of significance sig. in Table 4:13. Learn more about the F-test results of research can be seen below.
Table 4.13 Statistic F Test
ANOVA
a
Model Sum of
Squares df
Mean Square
F Sig.
1 Regression
1348.537 3
449.512 9.060
.000
b
Residual 2282.343
46 49.616
Total 3630.880
49 a. Dependent Variable: KPP
b. Predictors: Constant, KP, PP, KWP
Source: Data are processed From Table 4.13 shows that the calculated F value of 9.060 with
sig. is 0.000. This indicates that the regression model can be used to predict the performance values for the sig. 0.05. It can be concluded
Ha
4
received indicating that a significant difference between taxpayers consciousness, tax services, taxpayers compliance and simultaneously
to the tax revenue performance. d. The Result of Statistic t Test Partial Test
T test aims to determine how far the influence of the independent variables individually partial, the taxpayers consciousness, tax
services and taxpayers compliance in explaining the dependent variable, namely the tax revenue performance. Significance of the
74
regression model tested in this study by looking at sig. in the table 4:14. Learn more about the t-test results of research can be seen in the
following table.
Table 4.14 Statistic T Test
D a
r i
Source: Data are processed Decision making to accept or reject the hypothesis of each
independent variable as follows: 1. Ho accpected if
–t count - t table or t count t table 2. Ho rejected if
–t table t count t table With the results df n-k-1, the t table is 2.0129= tinv 0.05, 46
From table 4.14 above shows that the regression coefficient has a constant value of -10.572 with t value of -1.011 and sig. of 0.317.
Constant of -10.571 indicates that if the independent variables constant, the average tax revenue performance amounted to-10.571.
Coefficients
a
Model Unstandardized
Coefficients Standardized
Coefficients t
Sig. B
Std. Error Beta
1 Constant
-10.572 10.459
-1.011 .317
KWP .603
.270 .290
2.234 .030
PP .299
.134 .288
2.241 .030
KP .353
.167 .259
2.120 .039
a. Dependent Variable: KPP
