58
2 If there is no clear pattern, as well as the dots spread above and below zero 0 on the Y axis, then it indicates that there is no
heteroscedasticity or homocedasticity.
4. Hypothesis Test
a. Multiple Regression Test
Data processing activities is done by tabulating questionnaire by providing and summing the weights of the answers to each question
for each variable. Data analysis using multiple regression statistics techniques is to test the influence of variables independent on
dependent variable, that is, to find out the influence of modern taxation administration system implementation on taxpayer compliance, in KPP
Pratama Senen, Jakarta. Then, it check the plot of data for checking
there is any linear or non-linear data. The regression equations used is:
Y = α + β
1
X
1
+ β
2
X
2
+ β
3
X
3
+ β
4
X
4
+ ε Where:
Y : Taxpayer Compliance
α : Constant
β
1
X
1
: Organizational Structure β
2
X
2
: Organizational Procedure β
3
X
3
: Organizational Strategy β
4
X
4
: Organizational Culture ε
: Standard Error
59
b. Coefficient Determination Test Adjusted R
2
According to Wihandaru S. P., coefficient of determination R2 test is used to measure proportion of dependent variable variance
which is explained by independent variable. Determination coefficient is between zero and one. Small value of R2 is the ability of
independent variables explaining the dependent variable is very limited. Each additional one independent variable, then R2 is definitely
on the rise, no matter whether the variable has an effect on the dependent variable. Therefore, in this study the R Square use are
already adjusted R Square or Adjusted R2 due to the amount of adjusted variable used in the study. Value close to one means that the
variable-independent variable gives almost all the information needed to predict the variation in the dependent variable Ghozali, 2009:98.
c. Partial Regression Testing t-test
T test basically shows how far the influence of one independent variable individually in explaining the variation of dependent variable.
Probability is smaller than 0.05, then the result is significant means there is the influence of the independent variable individually on the
dependent variable Ghozali, 2009:164
d. Significant Simultaneous Test Test Statistic F
F test basically shows whether all independent variables included in the model have simultaneously effect on the dependent variable. The
probability is less than 0.05, then the result is significant means there is
