RUMUS : Y = (x1) + ( X2)
Reggresi Linear Ganda - one way anova
Regresi Linear Ganda digunakan untukmenganilisis perbedaan rata - rata lebih dari 2 sempel .
Alangkah lebih paham lagi jika kita langsung dengan mengerjakan CONTOH LATIHAN..!
- Akan dianalisi data yang bertujuan untuk mencari faktor yang berpengaruh terhadap tekanan sistolik tekanan darah (SBP). Dengan variabel predator : a. Usia ( AGE ) b. Berat Badan ( BB ), c. Riwayat Perokok.
|
No.
|
SBP
|
AGE
|
PEROKOK
|
BB
|
|
1.
|
144
|
45
|
0
|
75
|
|
2.
|
220
|
68
|
1
|
80
|
|
3.
|
138
|
45
|
0
|
70
|
|
4.
|
145
|
47
|
0
|
67
|
|
5.
|
162
|
65
|
1
|
75
|
|
6.
|
142
|
46
|
1
|
60
|
|
7.
|
170
|
67
|
1
|
70
|
|
8.
|
124
|
42
|
1
|
67 |
|
9.
|
158
|
67
|
1
|
76 |
|
10.
|
162
|
64
|
1
|
75 |
|
11.
|
150
|
56
|
1
|
67 |
|
12.
|
140
|
59
|
0
|
65 |
|
13.
|
110
|
34
|
0
|
66 |
|
14.
|
128
|
42
|
0
|
60 |
|
15.
|
130
|
48
|
0
|
67 |
|
16.
|
135
|
45
|
0
|
68 |
|
17.
|
114
|
17
|
0
|
60 |
|
18.
|
116
|
20
|
0
|
60 |
|
19.
|
124
|
19
|
0
|
60 |
|
20.
|
136
|
36
|
0
|
60 |
|
21.
|
142
|
50
|
1
|
67 |
|
22.
|
120
|
39
|
0
|
59 |
|
23.
|
120
|
21
|
0
|
58 |
|
24.
|
160
|
44
|
1
|
78 |
|
25.
|
158
|
53
|
1
|
70 |
|
26.
|
144
|
63
|
1
|
67 |
|
27.
|
130
|
29
|
0
|
68
|
|
28.
|
125
|
25
|
0
|
69
|
|
29.
|
175
|
69
|
1
|
80
|
|
30.
|
170
|
68
|
1
|
79
|
langkah - langkah :
- Buka program SPSS masukan data yang akan dianalisis kedalam tabel
- klik analyze pilih Regression pilih Linears
- muncul jendela Linears Regression pindahkan variabel SBP ke jendela DEPENDEN dan pindahkan variabel AGE, PEROKOK, BB ke jendela INDEPENDENT
- untuk mengerjakan ini ada 2 methode kita bisa pilih ( ENTER atau STEPWIS )
- klik ok ! maka muncul....
A. Metode ENTER
Metode ENTER digunakan untuk mengetahui 2 variabel yang berpengaruh dari 3 variabel dengan cara melihat nilai Asm.Sig yang paling rendah.
/METHOD=ENTER AGE Perokok BB.
Regression
[DataSet0]
|
Variables
Entered/Removedb
|
|||
|
Model
|
Variables Entered
|
Variables Removed
|
Method
|
|
1
|
BB, Perokok, AGEa
|
.
|
Enter
|
|
a. All requested variables entered.
|
|
||
|
b. Dependent Variable: SBP
|
|
||
|
Model Summary
|
||||
|
Model
|
R
|
R Square
|
Adjusted R Square
|
Std. Error of the
Estimate
|
|
1
|
.868a
|
.754
|
.725
|
12.079
|
|
a. Predictors: (Constant), BB, Perokok, AGE
|
||||
|
ANOVAb
|
||||||
|
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
|
|
|
1
|
Regression
|
11608.380
|
3
|
3869.460
|
26.521
|
.000a
|
|
Residual
|
3793.487
|
26
|
145.903
|
|
|
|
|
Total
|
15401.867
|
29
|
|
|
|
|
|
a. Predictors: (Constant), BB, Perokok, AGE
|
|
|
|
|||
|
b. Dependent Variable: SBP
|
|
|
|
|
||
|
Coefficientsa
|
||||||
|
Model
|
Unstandardized
Coefficients
|
Standardized
Coefficients
|
t
|
Sig.
|
||
|
B
|
Std. Error
|
Beta
|
||||
|
1
|
(Constant)
|
17.918
|
27.616
|
|
.649
|
.522
|
|
AGE
|
.550
|
.233
|
.387
|
2.359
|
.026
|
|
|
Perokok
|
7.813
|
6.442
|
.172
|
1.213
|
.236
|
|
|
BB
|
1.409
|
.478
|
.412
|
2.950
|
.007
|
|
|
a. Dependent Variable: SBP
|
|
|
|
|
||
Kesimpulan Metode ENTER :
Dari pengolahan data diatas dapat disimpulkan bahwa nilai :
Asm.Sig : AGE = 0,026 Perokok = 0,236 dan BB = 0,007
Maka, Faktor yang berpengaruh terhadap tekanan sistolik tekanan darah ( SBP ) adalah AGE dan BB
Karena nilai Asm.Sig paling rendah Diantara ke3 variabel tersebut.
B. Metode STEPWIS
Metode Stepwis untuk lebih Signifikan mengetahui 1 variabel yang sangat berpengaruh dari 2 variabel yang rendah dengan cara melihat nilai Asm.Sig
Regression
/METHOD=STEPWISE AGE Perokok BB.
[DataSet0]
|
Variables
Entered/Removeda
|
|||
|
Model
|
Variables Entered
|
Variables Removed
|
Method
|
|
1
|
AGE
|
.
|
Stepwise (Criteria:
Probability-of-F-to-enter <= ,050, Probability-of-F-to-remove >=
,100).
|
|
2
|
BB
|
.
|
Stepwise (Criteria:
Probability-of-F-to-enter <= ,050, Probability-of-F-to-remove >=
,100).
|
|
a. Dependent Variable: SBP
|
|
||
|
Model Summary
|
||||
|
Model
|
R
|
R Square
|
Adjusted R Square
|
Std. Error of the
Estimate
|
|
1
|
.803a
|
.646
|
.633
|
13.962
|
|
2
|
.860b
|
.740
|
.720
|
12.184
|
|
a. Predictors: (Constant), AGE
|
|
|||
|
b. Predictors: (Constant), AGE, BB
|
|
|||
|
ANOVAc
|
||||||
|
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
|
|
|
1
|
Regression
|
9943.338
|
1
|
9943.338
|
51.005
|
.000a
|
|
Residual
|
5458.529
|
28
|
194.947
|
|
|
|
|
Total
|
15401.867
|
29
|
|
|
|
|
|
2
|
Regression
|
11393.807
|
2
|
5696.903
|
38.377
|
.000b
|
|
Residual
|
4008.060
|
27
|
148.447
|
|
|
|
|
Total
|
15401.867
|
29
|
|
|
|
|
|
a. Predictors: (Constant), AGE
|
|
|
|
|
||
|
b. Predictors: (Constant), AGE, BB
|
|
|
|
|||
|
c. Dependent Variable: SBP
|
|
|
|
|
||
|
Coefficientsa
|
||||||
|
Model
|
Unstandardized
Coefficients
|
Standardized
Coefficients
|
t
|
Sig.
|
||
|
B
|
Std. Error
|
Beta
|
||||
|
1
|
(Constant)
|
90.023
|
7.853
|
|
11.464
|
.000
|
|
AGE
|
1.142
|
.160
|
.803
|
7.142
|
.000
|
|
|
2
|
(Constant)
|
8.927
|
26.833
|
|
.333
|
.742
|
|
AGE
|
.702
|
.198
|
.494
|
3.541
|
.001
|
|
|
BB
|
1.491
|
.477
|
.436
|
3.126
|
.004
|
|
|
a. Dependent Variable: SBP
|
|
|
|
|
||
|
Excluded Variablesc
|
||||||
|
Model
|
Beta In
|
t
|
Sig.
|
Partial Correlation
|
Collinearity
Statistics
|
|
|
Tolerance
|
||||||
|
1
|
Perokok
|
.231a
|
1.452
|
.158
|
.269
|
.480
|
|
BB
|
.436a
|
3.126
|
.004
|
.515
|
.496
|
|
|
2
|
Perokok
|
.172b
|
1.213
|
.236
|
.231
|
.471
|
|
a. Predictors in the Model: (Constant),
AGE
|
|
|
||||
|
b. Predictors in the Model: (Constant),
AGE, BB
|
|
|
||||
|
c. Dependent Variable: SBP
|
|
|
|
|||
Kesimpulan Metode STEPWIS :
Dari pengolahan data diatas dapat disimpulkan bahwa nilai :
Asm.Sig : AGE = 0,001 dan BB = 0,004
Maka, Faktor yang Sangat berpengaruh terhadap tekanan sistolik tekanan darah ( SBP ) adalah AGE
Karena nilai Asm.Sig paling rendah signifikan Diantara ke2 variabel tersebut.
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