LATIHAN
SOAL 1
HALAMAN 221
Lakukan
prediksi TRI dengan variabel Independet IMT, Umur dan Umur Kuadrat
a. Lakukan analisis Regresi masing-masing Independent variabel
b. Hitung SS Regression
c. Hitung SS for Residual
d. Hitung Mean SS for Regression
e. Hitung Mean SS for Residual
f. Hitung nilai F parsial
g. Hitung nilai r2
h. Buktikan penambahan X3 berperan
dalam memprediksi Y
|
TRI
|
IMT
|
UMUR
|
|
135
|
28
|
45
|
|
101
|
37
|
52
|
|
57
|
37
|
60
|
|
56
|
46
|
64
|
|
113
|
41
|
64
|
|
42
|
30
|
50
|
|
84
|
32
|
57
|
|
186
|
33
|
53
|
|
164
|
30
|
48
|
|
205
|
38
|
63
|
|
230
|
32
|
41
|
|
146
|
29
|
54
|
|
160
|
36
|
48
|
|
186
|
39
|
59
|
|
138
|
36
|
56
|
|
160
|
34
|
49
|
|
142
|
34
|
56
|
|
153
|
32
|
50
|
|
139
|
28
|
43
|
|
170
|
41
|
63
|
|
136
|
31
|
49
|
|
139
|
28
|
47
|
|
124
|
23
|
44
|
|
138
|
40
|
51
|
|
150
|
35
|
54
|
|
142
|
30
|
46
|
|
145
|
37
|
58
|
|
149
|
33
|
54
|
|
128
|
29
|
43
|
|
155
|
39
|
62
|
MODEL 1 :
TRI = β0 + β1 IMT
|
Variables Entered/Removedb
|
|||
|
Model
|
Variables Entered
|
Variables Removed
|
Method
|
|
1
|
Indeks
Massa Tubuha
|
.
|
Enter
|
|
a. All
requested variables entered.
|
|
||
|
b.
Dependent Variable: Trigliserida
|
|
||
|
Model Summary
|
||||
|
Model
|
R
|
R Square
|
Adjusted R Square
|
Std. Error of the Estimate
|
|
1
|
.057a
|
.003
|
-.032
|
41.696
|
|
a.
Predictors: (Constant), Indeks Massa Tubuh
|
||||
|
ANOVAb
|
||||||
|
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
|
|
|
1
|
Regression
|
160.067
|
1
|
160.067
|
.092
|
.764a
|
|
Residual
|
48678.633
|
28
|
1738.523
|
|
|
|
|
Total
|
48838.700
|
29
|
|
|
|
|
|
a.
Predictors: (Constant), Indeks Massa Tubuh
|
|
|
||||
|
b.
Dependent Variable: Trigliserida
|
|
|
|
|||
|
Coefficientsa
|
||||||
|
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
|
||
|
B
|
Std. Error
|
Beta
|
||||
|
1
|
(Constant)
|
154.991
|
52.922
|
|
2.929
|
.007
|
|
Indeks
Massa Tubuh
|
-.468
|
1.543
|
-.057
|
-.303
|
.764
|
|
|
a.
Dependent Variable: Trigliserida
|
|
|
|
|
||
MODEL 2 :
TRI = β0 + β1 UM
|
Model Summary
|
||||
|
Model
|
R
|
R Square
|
Adjusted R Square
|
Std. Error of the Estimate
|
|
1
|
.170a
|
.029
|
-.006
|
41.154
|
|
a.
Predictors: (Constant), Umur
|
|
|||
|
ANOVAb
|
||||||
|
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
|
|
|
1
|
Regression
|
1416.088
|
1
|
1416.088
|
.836
|
.368a
|
|
Residual
|
47422.612
|
28
|
1693.665
|
|
|
|
|
Total
|
48838.700
|
29
|
|
|
|
|
|
a.
Predictors: (Constant), Umur
|
|
|
|
|
||
|
b.
Dependent Variable: Trigliserida
|
|
|
|
|||
|
Coefficientsa
|
||||||
|
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
|
||
|
B
|
Std. Error
|
Beta
|
||||
|
1
|
(Constant)
|
193.196
|
59.636
|
|
3.240
|
.003
|
|
Umur
|
-1.025
|
1.121
|
-.170
|
-.914
|
.368
|
|
|
a.
Dependent Variable: Trigliserida
|
|
|
|
|||
MODEL 3 :
TRI = β0 + β1 UMKWT
|
Variables Entered/Removedb
|
|||
|
Model
|
Variables Entered
|
Variables Removed
|
Method
|
|
1
|
Umur Kuadrata
|
.
|
Enter
|
|
a. All
requested variables entered.
|
|
||
|
b.
Dependent Variable: Trigliserida
|
|
||
|
Model Summary
|
||||
|
Model
|
R
|
R Square
|
Adjusted R Square
|
Std. Error of the Estimate
|
|
1
|
.162a
|
.026
|
-.008
|
41.210
|
|
a.
Predictors: (Constant), Umur Kuadrat
|
|
|||
|
ANOVAb
|
||||||
|
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
|
|
|
1
|
Regression
|
1287.955
|
1
|
1287.955
|
.758
|
.391a
|
|
Residual
|
47550.745
|
28
|
1698.241
|
|
|
|
|
Total
|
48838.700
|
29
|
|
|
|
|
|
a.
Predictors: (Constant), Umur Kuadrat
|
|
|
|
|||
|
b.
Dependent Variable: Trigliserida
|
|
|
|
|||
|
Coefficientsa
|
||||||
|
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
|
||
|
B
|
Std. Error
|
Beta
|
||||
|
1
|
(Constant)
|
165.049
|
30.732
|
|
5.371
|
.000
|
|
Umur Kuadrat
|
-.009
|
.011
|
-.162
|
-.871
|
.391
|
|
|
a.
Dependent Variable: Trigliserida
|
|
|
| |||
MODEL 4 : TRI = β0 + β1 IMT + β2 UM
|
Variables Entered/Removedb
|
|||
|
Model
|
Variables Entered
|
Variables Removed
|
Method
|
|
1
|
Indeks
Massa Tubuh, Umura
|
.
|
Enter
|
|
a. All
requested variables entered.
|
|
||
|
b.
Dependent Variable: Trigliserida
|
|
||
|
Model Summary
|
||||
|
Model
|
R
|
R Square
|
Adjusted R Square
|
Std. Error of the Estimate
|
|
1
|
.215a
|
.046
|
-.024
|
41.536
|
|
a.
Predictors: (Constant), Indeks Massa Tubuh, Umur
|
||||
|
ANOVAb
|
||||||
|
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
|
|
|
1
|
Regression
|
2256.283
|
2
|
1128.141
|
.654
|
.528a
|
|
Residual
|
46582.417
|
27
|
1725.275
|
|
|
|
|
Total
|
48838.700
|
29
|
|
|
|
|
|
a.
Predictors: (Constant), Indeks Massa Tubuh, Umur
|
|
|
||||
|
b.
Dependent Variable: Trigliserida
|
|
|
|
|||
|
Coefficientsa
|
||||||
|
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
|
||
|
B
|
Std. Error
|
Beta
|
||||
|
1
|
(Constant)
|
188.027
|
60.643
|
|
3.101
|
.004
|
|
Umur
|
-2.075
|
1.883
|
-.345
|
-1.102
|
.280
|
|
|
Indeks
Massa Tubuh
|
1.785
|
2.558
|
.218
|
.698
|
.491
|
|
|
a.
Dependent Variable: Trigliserida
|
|
|
|
|
||
MODEL 5 :
TRI = β0 + β1 IMT + β2 UMKWT
|
Variables Entered/Removedb
|
|||
|
Model
|
Variables Entered
|
Variables Removed
|
Method
|
|
1
|
Umur kuadrat, Indeks Massa Tubuha
|
.
|
Enter
|
|
a. All
requested variables entered.
|
|
||
|
b.
Dependent Variable: Trigliserida
|
|
||
|
Model Summary
|
||||
|
Model
|
R
|
R Square
|
Adjusted R Square
|
Std. Error of the Estimate
|
|
1
|
.204a
|
.042
|
-.029
|
41.634
|
|
a.
Predictors: (Constant), Umur kuadrat, Indeks Massa TubuH
|
||||
|
ANOVAb
|
||||||
|
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
|
|
|
1
|
Regression
|
2036.327
|
2
|
1018.163
|
.587
|
.563a
|
|
Residual
|
46802.373
|
27
|
1733.421
|
|
|
|
|
Total
|
48838.700
|
29
|
|
|
|
|
|
a.
Predictors: (Constant), Umur kuadrat, Indeks Massa Tubuh
|
|
|
||||
|
b.
Dependent Variable: Trigliserida
|
|
|
|
|||
|
Coefficientsa
|
||||||
|
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
|
||
|
B
|
Std. Error
|
Beta
|
||||
|
1
|
(Constant)
|
133.975
|
56.573
|
|
2.368
|
.025
|
|
Indeks Massa Tubuh
|
1.706
|
2.597
|
.209
|
.657
|
.517
|
|
|
Umur kuadrat
|
-.019
|
.018
|
-.330
|
-1.040
|
.307
|
|
|
a.
Dependent Variable: Trigliserida
|
|
|
|
|
||
MODEL 6 :
TRI = β0 + β1 IMT + β2 UM + β3 UMKWT
|
Variables Entered/Removedb
|
|||
|
Model
|
Variables Entered
|
Variables Removed
|
Method
|
|
1
|
Umur, Indeks Massa Tubuh, Umur kuadrata
|
.
|
Enter
|
|
a. All
requested variables entered.
|
|
||
|
b.
Dependent Variable: Trigliserida
|
|
||
|
Model Summary
|
||||
|
Model
|
R
|
R Square
|
Adjusted R Square
|
Std. Error of the Estimate
|
|
1
|
.237a
|
.056
|
-.053
|
42.103
|
|
a.
Predictors: (Constant), Umur, Indeks Massa Tubuh, Umur kuadrat
| ||||
|
ANOVAb
|
||||||
|
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
|
|
|
1
|
Regression
|
2750.563
|
3
|
916.854
|
.517
|
.674a
|
|
Residual
|
46088.137
|
26
|
1772.621
|
|
|
|
|
Total
|
48838.700
|
29
|
|
|
|
|
|
a.
Predictors: (Constant), Umur, Indeks Massa Tubuh, Umur kuadrat
|
|
|||||
|
b.
Dependent Variable: Trigliserida
|
|
|
|
|||
|
Coefficientsa
|
||||||
|
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
|
||
|
B
|
Std. Error
|
Beta
|
||||
|
1
|
(Constant)
|
453.925
|
507.281
|
|
.895
|
.379
|
|
Indeks
Massa Tubuh
|
1.511
|
2.644
|
.185
|
.572
|
.573
|
|
|
Umur
kuadrat
|
.095
|
.180
|
1.685
|
.528
|
.602
|
|
|
Umur
|
-12.042
|
18.970
|
-2.000
|
-.635
|
.531
|
|
|
a.
Dependent Variable: Trigliserida
|
|
|
|
|
||
a. Y
= β0 + β1X1
TRI = β0 +
β1 IMT
TRI = 154.991 – 0.468 IMT =>
Nilai F hitung (0.092) < F tabel (4.2) maka Ho diterima sehingga dapat
disimpukan bahwa IMT tidak mempengaruhi TRIGLISERIDA.
Y = β0 +
β1X1
TRI = β0 +
β1 UM
TRI = 193.196 – 1.025 UM => Nilai
F hitung (0.836) < F tabel (4.2) maka Ho diterima sehingga dapat disimpukan
bahwa UMUR tidak mempengaruhi TRIGLISERIDA.
Y = β0 +
β1X1
TRI = β0 +
β1 UMKWT
TRI = 1287.955 + 47550.745 UMKWT
=> Nilai F hitung (0.758) < F tabel (4.2) maka Ho sehingga diterima dapat
disimpukan bahwa UMUR Kuadrat tidak mempengaruhi TRIGLISERIDA.
b. Nilai SS for Regression 
adalah 2750.563
adalah 2750.563
c. Nilai SS for
Residual adalah 46088.137
d. Nilai Means SS for Regression adalah
916.854
adalah
916.854
e. Nilai Means SS for Residual adalah 772.621
i. Nilai nilai F parsial adalah 0.517
j. Nilai r2 adalah 0.056
k. Buktikan penambahan 
berperan
dalam memprediksi Y
berperan
dalam memprediksi Y
TRI = 453.925 + 1.511 IMT – 12.042 UM +
0.095 UMKWT
Pada model 6 diatas, nilai F untuk
penambahan independen variabel X3 = 0.157 < F tabel (2.98),
ini berarti hipotesa Ho : β3 = 0 diterima atau gagal
ditolak, artinya penambahan Umur Kuadrat (X3) tidak secara bermakna
dapat memprediksi Y.
BAB 8
HALAMAN 187,188,189,191
Sudah Dikumpul/Dikerjakan Pada Tugas Pertemuan 10 dan
Tugas Pertemuan 11
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