PRAKTIKUM 11REGRESI LOGISTIK

Regresi logistic pada dasarnya sama dengan analisis regresi berganda dimana perbedaannya terletak pada variable independennya (variable terikatnya) merupakan VARIABEL DUMMY ( 0 dan 1).

PENGERTIAN

KARAKTERISTIK Variabel yang digunakan lebih dari 2

(MULTIVARIATE ANALISIS) Variabel Dependen : Variabel dummy 0 = gagal 1 = sukses Variabel independen : skala Interval/Rasio Tujuan :

Ingin mengetahui variabel independen mana yang mempengaruhi suatu perusahaan masuk dalam kelompok GAGAL dan SUKSES

CONTOH : File kasus 11.1 menunjukkan variabel-variabel yang digunakan untuk mempengaruhi kegagalan dan keberhasilan suatu perusahaan dengan variabel yang digunakan :Variabel Dependen : 0 = gagal 1= suksesVariabel Independen :

- Current Ratio (CR)- Return on ASET (ROA)- Return on Invesment (ROI)- Ukuran Perusahaan (FIRMSIZE)

- Corporate Social Responsibility (CSR)

Lakukan analisis regresi logistik dan interpretasikan hasil output tersebut sesuai dengan tujuan penelitian ini.

Pertanyaan

Klik Analyze, Reression, Binary Logistic

Pada variabel dependen : masukkan group

Pada covariates : masukkan semua variabel independent

Klik Option dan beri checklist seperti ditunjukkan pada gambar berikut :

Langkah-langkah :

HASIL PRINTOUTCase Processing Summary

Unweighted Casesa N Percent

Selected Cases Included in Analysis 50 100,0

Missing Cases 0 ,0

Total 50 100,0

Unselected Cases 0 ,0

Total 50 100,0

a. If weight is in effect, see classification table for the total number of cases.

Dependent Variable Encoding

Original Value Internal Value

Fail 0

Succeed 1

Iteration Historya,b,c

Iteration -2 Log likelihood

Coefficients

Constant

Step 0 1 67,302 ,400

2 67,301 ,405

3 67,301 ,405

a. Constant is included in the model.

b. Initial -2 Log Likelihood: 67,301

c. Estimation terminated at iteration number 3 because parameter

estimates changed by less than ,001.

Classification Tablea,b

Observed

Predicted

group Percentage

CorrectFail Succeed

Step 0 group Fail 0 20 ,0

Succeed 0 30 100,0

Overall Percentage 60,0

a. Constant is included in the model.

b. The cut value is ,500

Variables in the Equation

B S.E. Wald df Sig. Exp(B)

Step 0 Constant ,405 ,289 1,973 1 ,160 1,500

Variables not in the Equation

Score df Sig.

Step 0 Variables cr 29,519 1 ,000

roa 26,034 1 ,000

roi 29,852 1 ,000

firmsize 29,859 1 ,000

csr 40,412 1 ,000

Overall Statistics 45,512 5 ,000

Omnibus Tests of Model Coefficients

Chi-square df Sig.

Step 1 Step 67,301 5 ,000

Block 67,301 5 ,000

Model 67,301 5 ,000

Model Summary

Step -2 Log likelihood

Cox & Snell R

Square Nagelkerke R Square

1 ,000a ,740 1,000

a. Estimation terminated at iteration number 20 because maximum iterations

has been reached. Final solution cannot be found.

Hosmer and Lemeshow Test

Step Chi-square df Sig.

1 ,000 7 1,000

Contingency Table for Hosmer and Lemeshow Test

group = Fail group = Succeed

TotalObserved Expected Observed Expected

Step 1 1 5 5,000 0 ,000 5

2 5 5,000 0 ,000 5

3 5 5,000 0 ,000 5

4 5 5,000 0 ,000 5

5 0 ,000 5 5,000 5

6 0 ,000 5 5,000 5

7 0 ,000 5 5,000 5

8 0 ,000 5 5,000 5

9 0 ,000 10 10,000 10

Classification Tablea

Observed

Predicted

group Percentage

CorrectFail Succeed

Step 1 group Fail 20 0 100,0

Succeed 0 30 100,0

Overall Percentage 100,0

a. The cut value is ,500

Variables in the Equation

B S.E. Wald df Sig. Exp(B)

95% C.I.for EXP(B)

Lower Upper

Step 1a Cr -1,703 8433,182 ,000 1 1,000 ,182 ,000 .

Roa 1,007 1528,366 ,000 1 ,999 2,738 ,000 .

Roi ,383 3838,481 ,000 1 1,000 1,467 ,000 .

Firmsize ,284 1888,960 ,000 1 1,000 1,328 ,000 .

Csr 1,423 963,622 ,000 1 ,999 4,148 ,000 .

Constant -41,727 78370,624 ,000 1 1,000 ,000

a. Variable(s) entered on step 1: cr, roa, roi, firmsize, csr.

Correlation Matrix

Constant cr roa roi firmsize csr

Step 1 Constant 1,000 -,964 -,870 -,956 ,881 ,631

cr -,964 1,000 ,866 ,909 -,895 -,526

roa -,870 ,866 1,000 ,882 -,942 -,575

roi -,956 ,909 ,882 1,000 -,944 -,766

firmsize ,881 -,895 -,942 -,944 1,000 ,637

csr ,631 -,526 -,575 -,766 ,637 1,000