89 Figure 11. Pie Chart of Learning Style
Based on the result, it could be concluded that the Learning Style X Accounting Student at SMK Negeri 1 Yogyakarta academic year
20152016 was in the medium category.
C. Prerequisite Test Analysis
1. Linearity Test
Linearity test could be determined by using coefficient F. Coefficient F in this analysis is the nominal of coefficient F on the Deviation line from
Linierity which is figured in ANOVA Table. The relationship between independent variable and dependent variable is positive linear if F
count
F
table.
F
table
in this research is 2,53 with df1 is 4 k-1 and df2 is 58 n-k, that is the amount of research variables those are 4 independent variables
and 1 dependent variable, meanwhile n is the number of research respondents as much as 63. Based on the data analysis result on the
attachment 9, the linearity test result was as follows.
65.08 34.92
Learning Style
High Medium
Low
90 Table 22
. Summary of Test’s Linearity Result No
Variable F
count
F
table
Sig Conclusion
Independent Dependent 1
X
1
Y 1,715
2,53 0,071
Linear 2
X
2
Y 1,567
2,53 0,119
Linear 3
X
3
Y 1,031
2,53 0,444
Linear 4
X
4
Y 1,537
2,53 0,122
Linear Source: Primary data which were processed, 2016
Based on the table, from the calculation of each variable, F
count
is less than F
table.
Meanwhile the significance from each variable was more than 0,05, so that all the relationship structure between independent variable
and dependent variable was positive linear.
2. Multicolinearity Test
Multicolinearity test is used as the requirement of square regression. Multicolinearity test was aimed to see whether there is any intercorelation
among the independent variables. Multicolinearity test analysis can be observed by tolerance value and variance inflation factor VIF. Tolerance
value is the number of faulty level which can still determined as right statistically, meanwhile variance inflation factor VIF value is squared
raw deviation irregularity inflation factor. If tolerance 0,10 and Variance Inflation Factor VIF 10 so that can be concluded there is not
multicolinearity. Meanwhile, if tolerance 0,10 and Variance Inflation Factor VIF 10 so that can be concluded there is multicolinearity.
Multicolinearity test result by using SPSS version 23 for windows was shortly figured in the table below.
91 Table 23
. Summary of Test’s Multicolinierity Result Variable
VIF Tolerance
Conclusion X
1
1,981 0,505
There is no multicolinearity X
2
2,091 0,478
There is no multicolinearity X
3
2,823 0,354
There is no multicolinearity X
4
2,709 0,369
There is no multicolinearity Source: Primary data which were processed, 2016
The table shows that tolerance of each independent variable 0,10 and Variance Inflation Factor VIF 10 so that can be concluded that
there was no multicolinearity in this study so the research could not be continued.
D. Hypothesis Test
