Source: primary data questions obtained the lowest score is 41 and the highest score was 56. From the
data obtained the average price mean of 51.72, the middle value median of 52, mode of 56, and the deviation deviation SD of 3.397.
Table 7. Frequency Distribution Table Variable Data Entrepreneurship Interests
no Interval Class
Frequency Cumulative Frequency
Relative Frequency
Cumulative Frequency
1 41 to 42.9
1 1
1 1
2 43 to 44.9
3 4
3 4
3 45 to 46.9
7 11
7 11
4 47 to 48.9
6 17
6 17
5 49 to 50.9
13 30
13 30
6 51 to 52.9
23 53
23 53
7 53 to 54.9
26 79
26 79
8 55 to 56.9
21 100
21 100
total 100
100
Figure 1. Histogram Interests Entrepreneurship
Then identified the high and low propensity or variable interest entrepreneurship by using the mean value of the ideal Mi and the standard
deviation of the ideal SDI. Mi = ½ max score of the ideal - an ideal skormin = ½ 56-14 = 21
SD = 16 max score of the ideal - an ideal balanced min = 16 56-14 = 7
Table 8 propensity variable frequency Entrepreneurship Interests
No .
Tendency Interval
Class Frequency
Relative Cumulative
Information 1
Mi + 1 SDI 29
100 100
100 High
2 Mi-1SDi
toMi + 1 SDI 14-29
Moderate 3
Mi - 1SDi 14
Low total 100
Source: primary data Where: Mi SDI + 1 = 21 + 7 = 29
Mi - 1 SDI = 21-7 = 14
5 10
15 20
25 30
Interval Kelas Frekuensi
The table above shows that there are 100 100 of students have a high interest in entrepreneurship, 0 students are in the moderate tendency
Entrepreneurship Interests, and 0 students with low interest entrepreneurship. From these data it can be concluded most of the interest of
students to entrepreneurship is high.
2. Knowledge Entrepreneurship
Data Knowledge Entrepreneurship in the form of the value of entrepreneurship courses obtained from the Service Siakad UNY by admin
PUSKOM obtained the lowest score is 3.00 and the highest value is 4.00. From the data obtained the average price mean of 3.8, the middle value median of
4, mode mode of 4, and the deviation deviation SD of 0.268.
Table 9. Frequency Distribution of Variable Data Knowledge Entrepreneurship
no Interval
Class Frequency Cumulative
Frequency Relative
Frequency Cumulative
Frequency
1 3.00 to 3.13
2 2
2 2
2 3.14 to 3.27
2 2
3 3.28 to 3.31
2 2
4 3.32 to 3.45
15 17
15 17
5 3.46 to 3.59
17 17
6 3.60 to 3.73
32 49
32 49
7 3.74 to 3.87
49 49
8 3.88 to 4.00
51 100
51 100
number 100
100 Source: primary data
Figure 2. Histogram Entrepreneurship Knowledge
Then identified the high and low inclination or Knowledge Entrepreneurship variable based on UNY Academic Regulations as follows:
Table 10. Variable frequency distribution table tendency Knowledge Entrepreneurship
No. Interval
Class Frequency Percent
Cumulative Information
1 2.00 to 2.75
Satisfactory 2
2.76 to 3.50 17
17 17
Highly Satisfactory
3 3.51 to 4.00
83 83
100 Cumlaude
total 100
100 Source: primary data
The table above shows that there are 83 83 of students have knowledge of With Compliments entrepreneurship with honors, 17 students have knowledge of
entrepreneurship with honors, and 0 students have knowledge of entrepreneurship to Satisfy predicate.
2 15
32 51
Entrepreneurship Knowledge
3. Family Environment
Environmental Data Family X2 was obtained from a questionnaire consisting of 15 items query view using a modified Likert scale with four alternative
answers, the highest score is 4 and for the lowest score is 1. Of the questions obtained the lowest score is 41 and the highest score was 52. From the data obtained
the average price mean of 48.93, the middle value median of 49, mode mode of 52, and the deviation deviation SD of 2.872.
Table 11. Frequency Distribution Table Variable Data Environment Family
no Interval
Class Frequency Cumulative
Frequency Relative
Frequency Cumulative
Frequency
1 39.8 -41.6
1 1
1 1
2 41.7 to 43.5
1 2
1 2
3 43.6 to 45.4
13 15
13 15
4 45.5 to 47.3
16 31
16 31
5 47.4 to 49.2
22 53
22 53
6 49.3 to 51.1
18 71
18 71
7 51.2 to 53.0
29 100
29 100
8 53.8 to 55.6
100 100
number 100
100 Source: primary data
Figure 3. Histogram Family Environment
Then identified low or high propensity Family Environment variables using the mean value of the ideal Mi and the standard deviation of the ideal SDI.
Mi = ½ max score of the ideal - an ideal skormin = ½ 56-14 = 21 SD = 16 max score of the ideal - an ideal balanced min = 16 56-14 = 7
Table 12. Table propensity variable frequency Family Environment
No. Tendency
Interval Class
Frequency Relative
Cumulative Information
1 Mi + 1
SDI 29
100 100
100 High
2 Mi-1 SDi
to Mi + 1 SDi
14 -29 100
Moderate 3
Mi -
1SDi 14
100 Low
total 100 100
Source: primary data Where: Mi SDI + 1 = 21 + 7 = 29
5 10
15 20
25 30
39,8 - 41,6
41,7 – 43,5
43,6 – 45,4
45,5 – 47,3
47,4 – 49,2
49,3 – 51,1
51,2 – 53,0
53,8 – 55,6
Family Environment
Frekuensi
Mi - 1 SDi = 21-7 = 14 The table above shows that there are 100 100 of students have high Influence
of Family Environment, 0 students are in a Family Environment Influence tendency being, as well as students who have a 0 Environmental Effects of a low family. From
these data it can be concluded most of the Effect of Family Environment Student is high.
B. Prerequisites Testing Analysis
1. Normality Test
Normality test is used to determine whether the data generated from each variable is a variable with a normal distribution or not. Normality test is used to
analyze kolmogorov-smirno. Results calculated with SPSS greater than 0.05 at the 0.05 significance level. Here are the results of tests of normality:
Table 13. Normality Test Results Summary Table
variable
A
Kolmogorov-Smirnov information
N sig
Interest in Entrepreneurship
100 .175 normal
Family environment 100
.143 normal Based on the above table it is known that the results of calculations
using SPSS exceed 0.05 at significance level of 0.05, it can be concluded the data were normally distributed.
2. Linearity test
Linearity test is performed to determine whether the association of independent variables X and dependent variable Y in the form of linear or
not. The criteria is that if the price of the F count more than the F table at a significance level of 5, then the relationship of independent variables X
and dependent variable Y is expressed linearly. After calculating the premises of computer assistance program SPSS 17, the linearity test results
are summarized in the following table:
Table 14. Resume Linearity Test Results
variable Db
F F
count
Price F
table
Conclusion P
Sig
value
X
1
296 – Y
2.483 3.09 0,089
0.05 linear
X
2
989 – Y
1,253 1.98 0,274
00:05 linear
Source: primary data Based on the table above, the value of the significance of the effect of
independent variables X
1
and X
2
with the dependent variable Y is more than 0.05, and for the price of F
calculated
for each smaller than theF
table
3. Multicollinearity test
so it can be concluded that the two independent variables has a linear relationship
with the dependent variable.
Intended to determine how much the relationship between the independent variable. Based on Sofyan Yamin, 2011:50 Multicollinearity
is not the criteria if the VIF value is less than 10. Analysis is performed using the SPSS 17.0 computer program can be seen the following results:
Table 15.summary of the test results multicollinearity
variable VIF
information Knowledge
Entrepreneurship 1,635
not occur multicollinearity
Family Environment
1,635 not occur
multicollinearity Source: primary data
Based on the above table it is known that no VIF value greater than 10, it can be concluded that each variable multicollinearity problem does not
occur.
4. Heteroskidastity Test
Heteroskidastity test aims to test whether the regression model of the residual variance inequality occurs one other observation to
observation. Regression models were good then there is no heteroscedasticity. Heteroscedasticity does not happen, if the
t
value is smaller than t
table
and significance values greater than 0.05. Here is a summary of the heteroscedasticity test
Table 16. Test Results Table Heteroskidastity
variable sig
information Knowledge
Entrepreneurship 0.595
no problems heteroskedasticity
Family Environment
0.743 no problems
heteroskedasticity Source: primary data
