Uji Asumsi Klasik
Pengaruh Umur Siswa dan Tinggi Badan terhadap Nilai
Siswa
Variabel Terikat
(Dependent Variabel):
Nilai Siswa
Variabel
Bebas (Independent Variabel)
-
Umur
Siswa
-
Jenis
Kelamin Siswa
1.
Uji
Normalitas
Titik-titik pada
grafik berada disekitar garis diagonal dan tidak menjauh dari garis. Sehingga,
data penelitian ini lulus uji
normalitas.
2.
Uji
Multikolinearitas
Tujuannya untuk
dianalisis melalui tabel koofisien.
Variabel jenis
kelamin 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 umur
siswa :
Nilai tolerance =
0,689. Nilai tolerance > 0,1, dan
Nilai VIF = 1,451.
Nilai VIF = < 10,
Maka variabel
Tinggi Badan 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 SPSS
|
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
|
|||||
|
1
|
,499a
|
,249
|
,160
|
3,55812
|
,249
|
2,816
|
|
Model
Summaryb
|
|||
|
Model
|
Change
Statistics
|
||
|
df1
|
df2
|
Sig. F
Change
|
|
|
1
|
2a
|
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.
|
||
|
B
|
Std. Error
|
Beta
|
||||
|
1
|
(Constant)
|
70,452
|
9,733
|
|
7,239
|
,000
|
|
Jenis Kelamin Siswa
|
2,899
|
1,917
|
,383
|
1,512
|
,149
|
|
|
Umur Siswa
|
,344
|
,509
|
,171
|
,675
|
,509
|
|
|
Coefficientsa
|
|||
|
Model
|
Collinearity
Statistics
|
||
|
Tolerance
|
VIF
|
||
|
1
|
(Constant)
|
|
|
|
Jenis Kelamin Siswa
|
,689
|
1,451
|
|
|
Umur Siswa
|
,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
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