Uji Asumsi Klasik
Pengaruh Umur Siswa dan Jenis Kelamin terhadap Nilai
Siswa
Variabel Terikat (Dependent Variabel) :
- Nilai Siswa
Variabel Bebas
(Independent Variabel) :
- Umur Siswa
- Jenis Kelamin
Siswa
Titik-titik pada grafik berada disekitar garis
diagonal dan tidak menjauh dari garis. Sehingga, data penelitian ini lulus uji normalitas.
2.
Uji Multikolinearitas
Coefficientsa
|
||||||||
Model
|
Unstandardized
Coefficients
|
Standardized
Coefficients
|
t
|
Sig.
|
Collinearity
Statistics
|
|||
B
|
Std.
Error
|
Beta
|
Tolerance
|
VIF
|
||||
1
|
(Constant)
|
70,452
|
9,733
|
7,239
|
,000
|
|||
JENIS KELAMIN SISWA
|
2,899
|
1,917
|
,383
|
1,512
|
,149
|
,689
|
1,451
|
|
UMUR SISWA
|
,344
|
,509
|
,171
|
,675
|
,509
|
,689
|
1,451
|
|
a. Dependent Variable: NILAI SISWA
|
||||||||
Variabel
umur siswa:
Nilai
tolerance : 0,689. Nilai tolerance > 0,1, dan
Nilai
VIF = 1,451. Nilai VIF = < 10,
Maka
variabel Umur Siswa lulus uji
Multikolinearitas.
Variabel
Jenis Kelamin siswa:
Nilai
tolerance : 0,689. Nilai tolerance > 0,1, dan
Nilai
VIF = 1,451. Nilai VIF = < 10,
Maka
variabel Jenis Kelamin Siswa lulus
uji Multikolinearitas
3.
Uji Heteroskedastisitas
Titik
titik pada grafik tidak membentuk suatu pola tertentu yang teratur. Dan
menyebar di atas dan di bawah angka 0 pada sumbu Y. Maka, data penelitian ini lulus uji heteroskedastisitas.
LAMPIRAN
OUTPUT DARI SPSS
REGRESSION
/MISSING LISTWISE
/STATISTICS COEFF OUTS R ANOVA COLLIN TOL CHANGE
/CRITERIA=PIN(.05) POUT(.10)
/NOORIGIN
/DEPENDENT NILAI
/METHOD=ENTER GENDER UMUR
/SCATTERPLOT=(*SRESID ,*ZPRED)
/RESIDUALS NORMPROB(ZRESID).
Regression
[DataSet1] D:\Documents\SEMESTER 6\Komputer\tugas
uji asumsi klasik.sav
Variables
Entered/Removeda
|
|||
Model
|
Variables
Entered
|
Variables
Removed
|
Method
|
1
|
UMUR SISWA, JENIS KELAMIN SISWAb
|
.
|
Enter
|
a. Dependent Variable: NILAI SISWA
|
|||
b. All requested variables entered.
|
|||
Model
Summaryb
|
|||||||||
Model
|
R
|
R Square
|
Adjusted
R Square
|
Std.
Error of the Estimate
|
Change
Statistics
|
||||
R Square
Change
|
F Change
|
df1
|
df2
|
Sig. F
Change
|
|||||
1
|
,499a
|
,249
|
,160
|
3,55812
|
,249
|
2,816
|
2
|
17
|
,088
|
a. Predictors: (Constant), UMUR SISWA, JENIS KELAMIN SISWA
|
|||||||||
b. Dependent Variable: NILAI SISWA
|
|||||||||
ANOVAa
|
||||||
Model
|
Sum of
Squares
|
df
|
Mean
Square
|
F
|
Sig.
|
|
1
|
Regression
|
71,294
|
2
|
35,647
|
2,816
|
,088b
|
Residual
|
215,224
|
17
|
12,660
|
|||
Total
|
286,518
|
19
|
||||
a. Dependent Variable: NILAI SISWA
|
||||||
b. Predictors: (Constant), UMUR SISWA, JENIS KELAMIN SISWA
|
||||||
Coefficientsa
|
||||||||
Model
|
Unstandardized
Coefficients
|
Standardized
Coefficients
|
t
|
Sig.
|
Collinearity
Statistics
|
|||
B
|
Std.
Error
|
Beta
|
Tolerance
|
VIF
|
||||
1
|
(Constant)
|
70,452
|
9,733
|
7,239
|
,000
|
|||
JENIS KELAMIN SISWA
|
2,899
|
1,917
|
,383
|
1,512
|
,149
|
,689
|
1,451
|
|
UMUR SISWA
|
,344
|
,509
|
,171
|
,675
|
,509
|
,689
|
1,451
|
|
a. Dependent Variable: NILAI SISWA
|
||||||||
Collinearity
Diagnosticsa
|
||||||
Model
|
Dimension
|
Eigenvalue
|
Condition
Index
|
Variance
Proportions
|
||
(Constant)
|
JENIS
KELAMIN SISWA
|
UMUR
SISWA
|
||||
1
|
1
|
2,636
|
1,000
|
,00
|
,04
|
,00
|
2
|
,360
|
2,704
|
,00
|
,68
|
,00
|
|
3
|
,003
|
28,830
|
1,00
|
,28
|
1,00
|
|
a. Dependent Variable: NILAI SISWA
|
||||||
Residuals
Statisticsa
|
|||||
Minimum
|
Maximum
|
Mean
|
Std.
Deviation
|
N
|
|
Predicted Value
|
76,2929
|
81,2528
|
78,7900
|
1,93709
|
20
|
Std. Predicted Value
|
-1,289
|
1,271
|
,000
|
1,000
|
20
|
Standard Error of Predicted Value
|
1,125
|
1,938
|
1,363
|
,206
|
20
|
Adjusted Predicted Value
|
76,1758
|
81,7153
|
78,7247
|
1,92506
|
20
|
Residual
|
-6,10920
|
4,02000
|
,00000
|
3,36565
|
20
|
Std. Residual
|
-1,717
|
1,130
|
,000
|
,946
|
20
|
Stud. Residual
|
-1,827
|
1,191
|
,008
|
1,018
|
20
|
Deleted Residual
|
-6,91528
|
4,53564
|
,06534
|
3,90549
|
20
|
Stud. Deleted Residual
|
-1,977
|
1,207
|
-,015
|
1,059
|
20
|
Mahal. Distance
|
,950
|
4,684
|
1,900
|
,907
|
20
|
Cook's Distance
|
,000
|
,147
|
,053
|
,051
|
20
|
Centered Leverage Value
|
,050
|
,247
|
,100
|
,048
|
20
|
a. Dependent Variable: NILAI SISWA
|
|||||
Charts
