86 Table 26. Categorization of Parents Concern Tendency
No Limitation
Frequency Categorization
1 59.08
12 19,0
High 2
45.87-59.08 41
65,1 Enough
3 45.87
6 9,5
Low Total
63 100.0
The above table shows that students who have high Parents Concern is 19, enough of Parents Concern is 65,1 and Low
of Parents Concern is 9,5. Based on the category of varying Parents Concern tendency
in the table 26 can be described in the following Pie Chart.
Image 9. Pie Chart of Parents Concern Tendency
3. Analysis Prerequisite Test
a. Linearity Test
Linearity test used to determine if each independent variable X had a relationship or not with a dependent variable
Y, if not, the linear regression analysis cannot be extended. The criteria is when the price of F
Value
F
able
on 5 significance level,
87 then the relationship of the independent variables X with
dependent variable Y is expressed in linear. After the calculation is performed by computer data processing application programs,
such as linearity test results summarized in the following table: Table 27. Summarizing of Linearity Test Result
No Variable
F
value
F
table
Result Independent
Dependent
1 X1
Y 1.845
2.761 Linear
2 X2
Y 1.682
2.761 Linear
3 X3
Y 1.283
2.761 Linear
Source: Primary data that have been processed Table 27 shows that F
value
each variable is smaller than F
table
with 5 significant level. This applies to all independent variables, therefore it can be concluded that all independent variables have a
linear relationship with dependent variable.
b. Multicollinearity Test
Multicollinearity test used to find out whether or not there is Multicollinearity between independent variables as terms of use
of double regression in the fourth test the hypothesis. Multicollinearity does not occur is if the price inter correlation
each independent variable 0.600. There are least multicollinearity may be determined by t
he value of tolerance α and Variance Inflation Factor VIF Variable non experienced multicollinearity if
α value α and VIF value VIF and instead. Multicollinearity in summary test results are presented in the following table :
88 Table 28. Summarizing of Multicollinearity Test
Variable Collinearity Statistics
Result Tolerence
VIF X1
0.910 1.098
There is no multicollienarity
X2 0.967
1.025 X3
0.933 1.072
Source: Primary Data that have been processed If using alpha alphatolerance = 10 or 0.10, so VIF = 10. On table
26 is showing that VIF value VIF X
1
= 1.098, VIF X
2
= 1.025 and VIF X
3
=1.072 10 and independent variable tolerance X1= 0.910 = 91.0, X2=0.967 = 96.7, X3 = 0.933 = 93.3 more
than 10, can conclude that independent variable each other does not multicollinearity.
4. Research Hypothesis Test
