halaman 221
Lakukan
prediksi TRI dengan variabel independent IMT, Umur dan Umur kuadrat bekerjasama
di Laboraturium.
a.
Lakukan
analisa regresi masing-masing independent variabel
b.
Hitung
SS for regression (X3|X1,X2)
c.
Hitung
SS for residual
d.
Hitung
Means SS for regression (X3|X1,X2)
e.
Hitung
Means SS for residual
f.
Hitung
nilai F Parsial
g.
Hitung
nilai r2
h.
Bukti
penambahan X3 Berperan dalam memprediksi Y.
|
TRI
|
IMT
|
UM
|
TRI
|
IMT
|
UM
|
TRI
|
IMT
|
UM
|
|
135
|
28
|
45
|
230
|
32
|
41
|
136
|
31
|
49
|
|
101
|
37
|
52
|
146
|
29
|
54
|
139
|
28
|
47
|
|
57
|
37
|
60
|
160
|
36
|
48
|
124
|
23
|
44
|
|
56
|
46
|
64
|
186
|
39
|
59
|
138
|
40
|
51
|
|
113
|
41
|
64
|
138
|
36
|
56
|
150
|
35
|
54
|
|
42
|
30
|
50
|
160
|
34
|
49
|
142
|
30
|
46
|
|
84
|
32
|
57
|
142
|
34
|
56
|
145
|
37
|
58
|
|
186
|
33
|
53
|
153
|
32
|
50
|
149
|
33
|
54
|
|
164
|
30
|
48
|
139
|
28
|
43
|
128
|
29
|
43
|
|
205
|
38
|
63
|
170
|
41
|
63
|
155
|
39
|
62
|
Jawaban
:
a.
Analisa Regresi masing-masing
independent variabel
Model
1. TRI = β0 + β1 IMT
|
Coefficientsa
|
||||||
|
Model
|
Unstandardized
Coefficients
|
Standardized
Coefficients
|
|
|||
|
B
|
Std. Error
|
Beta
|
t
|
Sig.
|
||
|
1
|
(Constant)
|
154.991
|
52.922
|
|
2.929
|
.007
|
|
Indeks Massa Tubuh
|
-.468
|
1.543
|
-.057
|
-.303
|
.764
|
|
|
a. Dependent Variable: Trigliserida
|
||||||
Estimasi model 1 : TRI
= 154.991
+
-.468 IMT
|
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
|
||||||||||
Model
2. TRI = β0 + β1 UM
|
Coefficientsa
|
||||||
|
Model
|
Unstandardized
Coefficients
|
Standardized
Coefficients
|
|
|||
|
B
|
Std. Error
|
Beta
|
t
|
Sig.
|
||
|
1
|
(Constant)
|
193.196
|
59.636
|
|
3.240
|
.003
|
|
Umur
|
-1.025
|
1.121
|
-.170
|
-.914
|
.368
|
|
|
a. Dependent Variable: Trigliserida
|
||||||
Estimasi model 2 : TRI
= 193.196
+ -1.025 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
|
||||||||||
Model
3. TRI = β0 + β1 UMSQ
|
Coefficientsa
|
||||||
|
Model
|
Unstandardized
Coefficients
|
Standardized
Coefficients
|
|
|||
|
B
|
Std. Error
|
Beta
|
t
|
Sig.
|
||
|
1
|
(Constant)
|
165.049
|
30.732
|
|
5.371
|
.000
|
|
Umur Kuadrat
|
-.009
|
.011
|
-.162
|
-.871
|
.391
|
|
|
a. Dependent Variable: Trigliserida
|
||||||
Estimasi model 3 : TRI
= 165.049
+ -.009 UMSQ
|
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
|
||||||||||
Model
4. TRI = β0 + β1 IMT + β2 UM
|
Coefficientsa
|
||||||
|
Model
|
Unstandardized
Coefficients
|
Standardized
Coefficients
|
|
|||
|
B
|
Std. Error
|
Beta
|
t
|
Sig.
|
||
|
1
|
(Constant)
|
188.027
|
60.643
|
|
3.101
|
.004
|
|
Indeks Massa Tubuh
|
1.785
|
2.558
|
.218
|
.698
|
.491
|
|
|
Umur
|
-2.075
|
1.883
|
-.345
|
-1.102
|
.280
|
|
|
a. Dependent Variable: Trigliserida
|
||||||
Estimasi model 4 : TRI = 188.027 + 1.785 IMT + -2.075 UM
|
Model Summary
|
||||||||||
|
Model
|
R
|
R Square
|
Adjusted R Square
|
Std. Error of the
Estimate
|
||||||
|
1
|
.215a
|
.046
|
-.024
|
41.536
|
||||||
|
a. Predictors: (Constant), Umur, Indeks
Massa Tubuh
|
||||||||||
|
ANOVAb
|
||||||||||
|
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
|
|||||
|
1
|
Regression
|
|
2
|
1128.141
|
.654
|
.528a
|
||||
|
Residual
|
46582.417
|
27
|
1725.275
|
|
|
|||||
|
Total
|
48838.700
|
29
|
|
|
|
|||||
|
a. Predictors: (Constant), Umur, Indeks
Massa Tubuh
|
||||||||||
|
b. Dependent Variable: Trigliserida
|
||||||||||
Model
5. TRI = β0 + β1 IMT + β2 UMSQ
|
Coefficientsa
|
||||||
|
Model
|
Unstandardized
Coefficients
|
Standardized
Coefficients
|
|
|||
|
B
|
Std. Error
|
Beta
|
t
|
Sig.
|
||
|
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
|
||||||
Estimasi model 5 : TRI = 133.975 + 1.706 IMT +
-.019 UMSQ
|
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
|
||||||||||
Model
6. TRI = β0 + β1 IMT + β2 UM + β3 UMSQ
|
Coefficientsa
|
||||||
|
Model
|
Unstandardized
Coefficients
|
Standardized
Coefficients
|
|
|||
|
B
|
Std. Error
|
Beta
|
t
|
Sig.
|
||
|
1
|
(Constant)
|
453.925
|
507.281
|
|
.895
|
.379
|
|
Indeks Massa Tubuh
|
1.511
|
2.644
|
.185
|
.572
|
.573
|
|
|
Umur
|
-12.042
|
18.970
|
-2.000
|
-.635
|
.531
|
|
|
Umur Kuadrat
|
.095
|
.180
|
1.685
|
.528
|
.602
|
|
|
a. Dependent Variable: Trigliserida
|
||||||
Estimasi model 6 : TRI = 453.925 + 1.511 IMT + -12.042 UM + .095 UMSQ
|
Model Summary
|
||||
|
Model
|
R
|
R Square
|
Adjusted R Square
|
Std. Error of the
Estimate
|
|
1
|
.237a
|
.056
|
-.053
|
42.103
|
|
a. Predictors: (Constant), Umur Kuadrat,
Indeks Massa Tubuh, Umur
|
||||
|
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 Kuadrat,
Indeks Massa Tubuh, Umur
|
||||||
|
b. Dependent Variable: Trigliserida
|
||||||
|
sumber
|
df
|
SS
|
MS
|
F
|
r2
|
|
x1
|
1
|
160,067
|
160,067
|
0,092
|
0,674
|
|
x2|x1
|
1
|
2096,216
|
2096,216
|
1,858115
|
|
|
x3|x2|x1
|
1
|
494,28
|
494,28
|
0,010725
|
|
|
residual
|
26
|
46.088,137
|
1.772,621
|
|
|
|
total
|
29
|
48.838,700
|
|
|
|
|
no.
|
Model Estimasi
|
F
|
r2
|
|
1
|
Y = 154.991 + -.468 IMT
(1.543)*
|
.092
|
.764
|
|
2
|
Y = 193.196 + -1.025 UM
(1.121)*
|
.836
|
.368
|
|
3
|
Y = 165.049 + -.009
UMSQ
(.011)*
|
.758
|
.391
|
|
4
|
Y = 188.027 + 1.785 IMT + -2.075 UM
(2.558)* (1.883)*
|
.654
|
.528
|
|
5
|
Y = 133.975 + 1.706 IMT +
-.019 UMSQ
(2.597)* (.018)*
|
.587
|
.563
|
|
6
|
Y = 453.925 + 1.511 IMT + -12.042 UM
+ .095 UMSQ
(2.644)* (18.970)* (.180)*
|
.517
|
.674
|
b. Nilai SS for
Regression 
adalah 494,28
adalah 494,28
c. Nilai SS for
Residual adalah
46088.137
d. Nilai Means
SS for Regression adalah 494,28
adalah 494,28
e. Nilai Means SS for Residual adalah 46.088,137
i. Nilai nilai F parsial adalah 0.517
j. Nilai r2 adalah 0,674
k. Buktikan penambahan 
berperan dalam memprediksi Y
berperan dalam memprediksi Y
Dari ke enam model
estimasi terlihat bahwa variable IMT secara konsisten sangat berpengaruh
terhadap TRI (p<0.05). pada model estimasi 1 tampak nilai r2
sebesar .764 dan bila dibandingkan dengan
model estimasi 4, 5, dan 6 penambahan nilai rr relatif kecil
masing-masing .528, .563, .674
atau hanya berkurang sebesar .236, .201 dan .09 ini sangat tidak berarti.
Dengan
demikian kita bisa berkesimpulan variable IMT sangat bermakna pengaruhnya
terhadap TRI. Sebaliknya penambahan variable UM dsan UMSQ tida berperan dalam
menjelaskan variasi TRI dan kita tidak perlu menambahkan kedua variable
tersebut ke dalam model. Model akhir yaitu : Y
= 154.991 + -.468 IMT
BAB 8
HAL 187,188 ,191 sudah di kirim/dikumpul di Tugas Pertemuan 10 dan Pertemuan 11
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