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D. Method of Data Analysis
The method of data analysis is a method used to process the research data by using the simplification of data in a form thatis easy to read and interpreted
Ghozali, 2011:5. The method used in this study is a quantitative method.To find out how much the level of consciousness of the taxpayer, the tax service
quality, and taxpayer compliance, variablesmeasurement tools required that is using scale model or called Likert type format. Likert method designed to
measure the level of consciousness, service, and compliance by answering
various questions about the variables that will be tested.
Development usage of procedures which represent a bipolar continuum. At the end of the left a small number represents a negative answer, while the
right end with a large number describing the positive. 1.
QualityTest Data
In a study to obtain valid and reliable data should be tested against the data. Instrument used for testing data are:
a. ValidityTest
The validity means that how far the precision and accuracy of a measuring instrument in doing the measuring function. A test or
measuring instrument can be said to have a high validity when measuring instrument doing their functions properly. Validity indicates
how farthe measuring device is able to measure what you want to measure.
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Testing the validity of the thesis is done by comparing the value of r count and r table for the degree of freedom df = n-2, in this case n is
the number of samples.
b. Reliability Test
If a measurement tools has been declared valid the next step is to measure the reliability of the tools. As a measure that shows the
consistency of the measuring instrument to measure the same phenomenon in other occasions. Reliability tests aim to see the
consistency of a measuring instrument will be used whether the gauge is accurate, stable, and consistent.
2. Classical Assumptions Test
In this classical assumption test that used is the normality test data, multicollinearity, autocorrelation and heteroscedasticity.
a. MulticollinearityTest Multicollinearity test aims to test whether the regression model found a
correlation between the independent variables independent. A good regression model,corelation should not happen between independent
variables Ghozali, 2011:91. To detect the presence or absence multicollinearity in the regression model can be seen from the amount
of the value of the Tolerance and VIF Variance Inflation Factor. Free regression from multicollinearity trouble if the Tolerance value 0.10
or equal to the value of VIF 10 Ghozali, 2011:92.
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b. HeteroscedasticityTest Heteroscedasticity test aims to test whether in the regression model
there is unequality variance from one residual observation to other observation. If the variance from one residual observation to another
observation is fixed, then it is called homokedastitas and if it is different called heteroscedasticity. A good regression model is a
regression model that is homokedastitas. Detection the presence ofheteroscedasticitycan be do by looking at whether there are a
particular pattern in scatterplot graph between the predictive value of the dependent variable ZPRED with the residual SRESID where
the Y axis is the predicted while X is residual. If there are certain patterns so that will indicate there has been heterokedestitas, but if
there is no clear pattern and the points spread above and below zero on the Y axis, so it heteroscedasticity does not happen Ghozali,
2011:105. c. Normality test
Normality test data aims to test whether the regression model, both independent and dependent variables, have been distributed normally.
Good regression models is regression model with normal distribution data or near normal. To determinewhether or not the normal
distribution of the data can be detected by looking Normality Probability Plot P-Plot. If the data dots spread around the diagonal
line and follow the direction of the diagonal line or line histogram,
Kategori