CONTOH DISERTASI ANALISIS JALUR LISREL
CONTOH DISERTASI / TESIS
PENGARUH BAURAN PEMASARAN (MIX MARKETING) TERHADAP EKUITAS
MERK (BRANDING EQUITY)
STUDI ANALISIS JALUR DENGAN LISREL
Processm
X5
Sponsorship
X1
r25
r56
r12
Brand
X6
r75
Promotion
X2
r13
e1
r17
e2
r36
r76
r14
r23
r18
Pricing
X3
r24
r37
Public Rel
X7
e3
r28
r34
r45
r78
r47
Power
X4
r48
Place
X8
e4
Gambar 7.7 The 8-factor path analysis of the marketing mix
Contoh hipotesis yang diajukan
a.
Terdapat pengaruh langsung positif sponsorship terhadap public relation
management
b.
Terdapat pengaruh langsung positif sponsorship terhadap placement management
c.
Terdapat pengaruh langsung positif promotion management terhadap management
process
d.
Terdapat pengaruh langsung positif management promotion terhadap placement
management
e.
Terdapat pengaruh langsung positif pricing management terhadap brand
mangement
f.
Terdapat pengaruh langsung positif pricing management terhadap public relation
management
g.
Terdapat pengaruh langsung positif power of the market terhadap management
process
h.
Terdapat pengaruh langsung positif power of the market terhadap public relation
management
i.
Terdapat pengaruh langsung positif power of the market terhadap placement
management
j.
Terdapat pengaruh langsung positif management process terhadap brand
management
k.
Terdapat pengaruh langsung positif public relation management terhadap brand
management
l.
Terdapat pengaruh langsung positif public relation management terhadap
management process
m.
Terdapat pengaruh langsung positif public relation management terhadap placement
management
n.
Terdapat pengaruh tidak langsung sponsorship terhadap management process
melalui public relation management
o.
Terdapat pengaruh tidak langsung sponsorship terhadap brand management
melalui public relation mangement
p.
Terdapat pengaruh tidak langsung positif sponsorship terhadap place management
melalui public relation mangement
q.
Terdapat pengaruh tidak langsung positif promotion management terhadap brand
management melalui process mangement
r.
Hipotesis pertama: Terdapat pengaruh tidak langsung positif pricing management
terhadap process management melalui public relation mangement
s.
Terdapat pengaruh tidak langsung positif pricing management terhadap brand
management melalui public relation mangement
t.
Terdapat pengaruh tidak langsung positif pricing management terhadap place
management melalui public relation mangement
u.
Terdapat pengaruh tidak langsung positif power of market management terhadap
process management melalui public relation mangement
v.
Terdapat pengaruh tidak langsung positif power of market management terhadap
brand management melalui public relation mangement dan process management
w.
Terdapat pengaruh tidak langsung positif power of market management terhadap
place management melalui public relation mangement
x.
Terdapat pengaruh tidak langsung public relation management terhadap brand
management melalui process mangement
1. Siapkan Menu PRELIS Data
1.1 Input data
Untuk menguji contoh hipotesis penelitian di atas, buka menu PRELIS Data pada editor
LISREL kemudian ikuti langkah sebagai berikut:
Klik File
Klik New
Klik PRELIS Data
Klik OK
Klik Data
Klik Define variabel
Klik Insert
Pada dialog box Add variables ketik X1-X8
Klik OK
Pada dialog box define variabel sudah terisi X1 X2 X3 X4 X5 X6 X7 X8 selanjutnya klik
OK
Gambar 7.8 Menu PRELIS Data
Klik Data
Klik Insert cases
Ketikkan jumlah responden yang akan diteliti (misal 124) klik OK
Gambar 7.9 Menu input data PRELIS
Terlihat editor PRELIS Data LISREL yang sudah siap diinput, Klik sel yang akan diisi
data sekali lagi data ini hanya untuk ilustrasi saja bukan hasil penelitian yang sebenarnya,
setelah itu input contoh data berikut:
Tabel 7.3 Contoh Data Penelitian
RESP
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
X1
186
159
220
144
163
153
218
197
173
177
188
157
183
224
158
129
148
142
196
166
184
137
145
162
164
217
171
195
176
201
169
162
170
183
X2
113
72
162
105
121
96
157
136
103
104
129
110
127
163
122
95
118
124
135
100
66
96
114
124
106
152
59
135
115
140
101
91
118
112
X3
119
98
154
61
84
117
152
137
69
114
129
105
126
158
85
72
115
123
135
116
111
115
118
82
117
152
89
135
104
139
107
101
110
98
X4
110
92
155
61
87
88
150
128
99
107
118
102
114
156
96
102
94
112
127
73
87
44
109
100
101
145
107
127
76
134
93
97
73
43
X5
164
188
178
225
202
149
193
158
223
191
229
163
182
168
162
134
153
147
201
171
189
142
150
167
169
222
176
200
181
206
174
167
175
188
X6
124
69
118
102
100
159
93
119
154
160
107
133
126
110
101
92
115
121
132
97
63
93
111
121
103
149
56
132
112
137
98
88
115
109
X7
90
132
125
104
75
120
135
158
91
164
67
143
160
111
123
78
121
129
141
122
117
121
124
88
123
158
95
141
110
145
113
107
116
104
X8
109
102
145
113
123
151
94
105
91
150
83
82
56
97
87
97
89
107
122
68
82
39
104
95
96
140
102
122
71
129
88
92
68
38
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
168
197
178
204
214
167
229
176
181
195
136
161
163
138
211
176
175
192
171
170
143
190
174
193
184
185
169
181
136
174
177
209
141
185
179
198
179
175
143
167
178
185
131
175
148
230
127
181
142
149
158
158
202
168
159
110
137
95
143
151
116
166
103
103
134
83
64
98
113
150
120
110
133
119
111
106
128
67
133
99
77
57
120
106
114
121
144
105
101
113
139
112
130
104
125
106
94
97
119
100
164
70
80
126
113
107
115
141
124
96
71
137
99
142
149
100
164
120
84
134
108
93
113
66
148
78
91
132
114
86
76
127
100
132
122
107
71
109
108
86
88
145
116
92
121
138
64
131
83
125
111
67
94
121
119
166
97
106
125
74
85
101
140
124
65
42
129
90
136
145
105
158
110
53
126
79
108
72
58
144
97
90
120
104
106
91
116
79
122
112
86
95
89
103
54
91
142
58
79
111
129
103
119
90
113
85
79
95
111
110
159
89
91
114
106
89
84
134
113
94
173
202
183
209
219
172
234
181
186
200
141
166
168
143
216
181
180
197
176
175
148
195
179
198
189
190
174
186
141
179
182
214
146
190
184
203
184
180
148
172
183
190
136
180
153
235
132
186
147
154
163
163
207
173
164
107
134
92
140
148
113
163
100
100
131
80
61
95
110
147
117
107
130
116
108
103
125
64
130
96
74
54
117
103
111
118
141
102
98
110
136
109
127
101
122
103
91
94
116
97
161
67
77
123
110
104
112
138
121
93
77
143
105
148
155
106
170
126
90
140
114
99
119
72
154
84
97
138
120
92
82
133
106
138
128
113
77
115
114
92
94
151
122
98
127
144
70
137
89
131
117
73
100
127
125
172
103
112
131
80
91
107
146
130
71
37
124
85
131
140
100
153
105
48
121
74
103
67
53
139
92
85
115
99
101
86
111
74
117
107
81
90
84
98
49
86
137
53
74
106
124
98
114
85
108
80
74
90
106
105
154
84
86
109
101
84
79
129
108
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
173
149
180
146
160
113
180
146
208
150
145
166
212
182
125
160
210
134
122
194
143
157
182
189
144
184
161
190
150
172
186
165
164
172
132
87
98
108
79
72
125
112
107
143
60
101
107
150
76
102
102
148
121
90
134
113
84
91
99
78
109
67
132
94
123
108
108
111
93
128
112
102
113
95
91
124
76
88
143
98
109
110
148
87
120
60
146
115
77
133
94
110
63
93
102
112
77
131
123
104
103
83
118
90
128
99
104
100
86
65
113
74
68
138
105
60
101
144
75
111
62
143
88
96
124
105
94
106
78
97
65
81
120
112
73
51
88
109
108
117
178
154
185
151
165
118
185
151
213
155
150
171
217
187
130
165
215
139
127
199
148
162
187
194
149
189
166
195
155
177
191
170
169
177
137
84
95
105
76
69
122
109
104
140
57
98
104
147
73
99
99
145
118
87
131
110
81
88
96
75
106
64
129
91
120
105
105
108
90
125
118
108
119
101
97
130
82
94
149
104
115
116
154
93
126
66
152
121
83
139
100
116
69
99
108
118
83
137
129
110
109
89
124
96
134
94
99
95
81
60
108
69
63
133
100
55
96
139
70
106
57
138
83
91
119
100
89
101
73
92
60
76
115
107
68
46
83
104
103
112
Setelah selesai menginput data, simpan terlebih dahulu raw data tersebut misalnya di drive D:
dengan nama file: MARKET.PSF, caranya klik File, klik Save As, pada dialog box File Save As,
klik D: pada kotak Drives kemudian klik pada kotak File name lalu ketikkan MARKET.PSF
akhiri dengan mengklik OK. Sebaliknya untuk membuka file yang sudah tersimpan, Klik File,
klik Open, pada kotak Drives: pilih D, pada kotak Save file as type pilih all files (*.*), pada
kotak File name tarik slider ke bawah klik MARKET.PSF akhiri dengan OK
Gambar 7.10 Menu Save As PRELIS
1.2 Analisis Deskripsi Data dan Normalitas Data
Setelah file MARKET.PSF terbuka selanjutnya untuk mengetahui deskripsi atau gambaran data
seperti normalitas data baik secara univariat maupun multivariat, histogram masing-masing
variabel, matrik korelasional, rerata (mean), dan simpangan baku antar variabel, dengan mudah
dapat dianalisis melalui menu PRELIS Data LISREL. Namun sebelum dianalisis, definisikan
terlebih dahulu jenis data yang akan dipakai, ini penting karena LISREL akan memperlakukan
variabel kategorikal yang terdistribusi secara normal dapat dianggap sebagai jenis data kontinyu.
Untuk itu ikuti langkah-langkah sebagai berikut:
Klik Data, pada editor PRELIS
Klik Define Variables
Pada kotak Define variables sudah berisi variabel X1 sd X8
Dengan menekan Ctrl (jangan dilepas) lalu klik X1 sd X8 terlihat berwarna biru
Lepas Ctrl, lalu klik Variable Type
Tampak beberapa pilihan tipe variabel, lalu klik Continous, klik OK
Setelah tipe variabel ditentukan langkah berikutnya menganalisis estimasi deskripsi masingmasing variabel menggunakan menu statistik pada PRELIS LISREL. Langkah-langkahnya
sebagai berikut:
Klik menu Statistics
Terlihat beberapa pilihan, untuk kali ini klik Output Option
Gambar 7.11 Menu Output Option PRELIS
Klik kotak pada LISREL system data
Klik kotak di bawah Moment Matrix pilh Correlations,
klik kotak Save the transformed data to file,
lalu ketikkan nama File misalnya DESKRIP,
klik kotak pada Perform tests of multivariate normality, yang lainnya abaikan,
akhiri dengan klik OK
Hasil output LISREL dapat dilihat sebagai berikut:
DATE: 03/04/2012
TIME: 19:09
LISREL 8.80 (STUDENT EDITION)
BY
Karl G. Jöreskog & Dag Sörbom
This program is published exclusively by
Scientific Software International, Inc.
7383 N. Lincoln Avenue, Suite 100
Chicago, IL 60646-1704, U.S.A.
Phone: (800)247-6113, (847)675-0720, Fax: (847)675-2140
Copyright by Scientific Software International, Inc., 1981-99
Use of this program is subject to the terms specified in the
Universal Copyright Convention.
Website: www.ssicentral.com
The following lines were read from file D:\MARKET.PR2:
!PRELIS SYNTAX: Can be edited
SY=D:\MARKET.PSF
OU MA=KM RA=MARKET.PR2 ME= SD= DESKRIP
Total Sample Size =
124
Univariate Summary Statistics for Continuous Variables
Variable
-------X1
X2
X3
X4
X5
X6
X7
X8
Mean
---171.274
111.234
108.790
100.597
176.274
108.234
114.790
95.597
St. Dev.
-------24.457
23.721
24.622
25.621
24.457
23.721
24.622
25.621
T-Value
------77.982
52.217
49.201
43.721
80.259
50.809
51.914
41.548
Skewness
-------0.125
-0.011
0.056
0.045
0.125
-0.011
0.056
0.045
Kurtosis
--------0.311
-0.110
-0.613
-0.127
-0.311
-0.110
-0.613
-0.127
Minimum Freq.
------- ----113.000
1
57.000
1
60.000
1
42.000
1
118.000
1
54.000
1
66.000
1
37.000
1
Maximum Freq.
------- ----230.000
1
166.000
1
166.000
1
159.000
1
235.000
1
163.000
1
172.000
1
154.000
1
Test of Univariate Normality for Continuous Variables
Skewness
Variable Z-Score P-Value
X1
X2
X3
X4
X5
X6
X7
X8
0.573
-0.052
0.255
0.207
0.573
-0.052
0.255
0.207
Kurtosis
Skewness and Kurtosis
Z-Score P-Value
0.566
0.958
0.799
0.836
0.566
0.958
0.799
0.836
-0.564
0.017
-1.714
-0.029
-0.564
0.017
-1.714
-0.029
Chi-Square P-Value
0.573
0.986
0.087
0.977
0.573
0.986
0.087
0.977
0.647
0.003
3.002
0.044
0.647
0.003
3.002
0.044
0.724
0.998
0.223
0.978
0.724
0.998
0.223
0.978
Relative Multivariate Kurtosis = 2.538
Test of Multivariate Normality for Continuous Variables
Skewness
Value
-----63.623
Z-Score P-Value
------- ------28.419
0.000
Kurtosis
Value
------124.317
Skewness and Kurtosis
Z-Score P-Value
------- ------13.037
0.000
Chi-Square P-Value
---------- ------977.577
0.000
Histograms for Continuous Variables
X1
Frequency Percentage Lower Class Limit
2
1.6
113.000
••
8
6.5
124.700
••••••••
16
12.9
136.400
••••••••••••••••
12
9.7
148.100
••••••••••••
23
18.5
159.800
•••••••••••••••••••••••
27
21.8
171.500
•••••••••••••••••••••••••••
15
12.1
183.200
•••••••••••••••
9
7.3
194.900
•••••••••
8
6.5
206.600
••••••••
4
3.2
218.300
••••
X2
Frequency Percentage Lower Class Limit
7
5.6
57.000
•••••••
6
4.8
67.900
••••••
5
4.0
78.800
•••••
18
14.5
89.700
••••••••••••••••••
28
22.6
100.600
••••••••••••••••••••••••••••
23
18.5
111.500
•••••••••••••••••••••••
15
12.1
122.400
•••••••••••••••
12
9.7
133.300
••••••••••••
5
4.0
144.200
•••••
5
4.0
155.100
•••••
X3
Frequency Percentage Lower Class Limit
8
6.5
60.000
••••••••
9
7.3
70.600
•••••••••
16
12.9
81.200
••••••••••••••••
17
13.7
91.800
•••••••••••••••••
20
16.1
102.400
••••••••••••••••••••
20
16.1
113.000
••••••••••••••••••••
14
11.3
123.600
••••••••••••••
9
7.3
134.200
•••••••••
8
6.5
144.800
••••••••
3
2.4
155.400
•••
X4
Frequency Percentage Lower Class Limit
5
4.0
42.000
•••••
8
6.5
53.700
••••••••
8
15
25
29
12
9
8
5
6.5
12.1
20.2
23.4
9.7
7.3
6.5
4.0
65.400
77.100
88.800
100.500
112.200
123.900
135.600
147.300
••••••••
•••••••••••••••
•••••••••••••••••••••••••
•••••••••••••••••••••••••••••
••••••••••••
•••••••••
••••••••
•••••
X5
Frequency Percentage Lower Class Limit
2
1.6
118.000
••
8
6.5
129.700
••••••••
16
12.9
141.400
••••••••••••••••
12
9.7
153.100
••••••••••••
23
18.5
164.800
•••••••••••••••••••••••
27
21.8
176.500
•••••••••••••••••••••••••••
15
12.1
188.200
•••••••••••••••
9
7.3
199.900
•••••••••
8
6.5
211.600
••••••••
4
3.2
223.300
••••
X6
Frequency Percentage Lower Class Limit
7
5.6
54.000
•••••••
6
4.8
64.900
••••••
5
4.0
75.800
•••••
18
14.5
86.700
••••••••••••••••••
28
22.6
97.600
••••••••••••••••••••••••••••
23
18.5
108.500
•••••••••••••••••••••••
15
12.1
119.400
•••••••••••••••
12
9.7
130.300
••••••••••••
5
4.0
141.200
•••••
5
4.0
152.100
•••••
X7
Frequency Percentage Lower Class Limit
8
6.5
66.000
••••••••
9
7.3
76.600
•••••••••
16
12.9
87.200
••••••••••••••••
17
13.7
97.800
•••••••••••••••••
20
16.1
108.400
••••••••••••••••••••
20
16.1
119.000
••••••••••••••••••••
14
11.3
129.600
••••••••••••••
9
7.3
140.200
•••••••••
8
6.5
150.800
••••••••
3
2.4
161.400
•••
X8
Frequency Percentage Lower Class Limit
5
4.0
37.000
•••••
8
6.5
48.700
••••••••
8
6.5
60.400
••••••••
15
12.1
72.100
•••••••••••••••
25
20.2
83.800
•••••••••••••••••••••••••
29
23.4
95.500
•••••••••••••••••••••••••••••
12
9.7
107.200
••••••••••••
9
7.3
118.900
•••••••••
8
6.5
130.600
••••••••
5
4.0
142.300
•••••
Correlation Matrix
X1
X2
X3
X4
X5
X6
X7
X8
X1
-------1.000
0.580
0.556
0.542
0.861
0.458
0.444
0.415
Correlation Matrix
X2
--------
X3
--------
X4
--------
X5
--------
X6
--------
1.000
0.668
0.627
0.456
0.850
0.562
0.505
1.000
0.722
0.369
0.556
0.879
0.595
1.000
0.387
0.510
0.619
0.864
1.000
0.448
0.357
0.400
1.000
0.588
0.560
X7
X8
X7
-------1.000
0.588
X8
--------
X1
-------171.274
X2
-------111.234
X7
-------114.790
X8
-------95.597
1.000
Means
X3
-------108.790
X4
-------100.597
X5
-------176.274
X6
-------108.234
X3
-------24.622
X4
-------25.621
X5
-------24.457
X6
-------23.721
Means
Standard Deviations
X1
-------24.457
X2
-------23.721
Standard Deviations
X7
-------24.622
X8
-------25.621
The Problem used
9496 Bytes (= 0.0% of available workspace)
1.3 Diskusi Statistik Deskripsi dan Normalitas Data
1). Hasil uji normalitas univariat variabel X1, X2, X3, X4, X5, X6, X7 dan X8, diperoleh
Zskewness dan Zkurtosis berada diantara -1.96 hingga +1,96. Sebagai contoh kita ambil variabel
X1 Zskewness = 0,566 dan Zkurtosis = -0.564 Dengan demikian nilai Zskewness dan Zkurtosis untuk
variabel X1 berada diantara -1,96 hingga +1,96 sehingga dapat disimpulkan bahwa data
variabel X1 cenderung berdistribusi normal. Demikian juga nilai Pskewness maupun Pkurtosis
untuk variabel berturut-turut 0.566 dan 0.573 lebih besar dari α = 0,05 sehingga dapat
disimpulkan bahwa data variabel X1 cenderung berdistribusi normal.
2). Matrik koefisien korelasi antar variabel semuanya bernilai positif sehingga dapat dilanjutkan
sebagai data input untuk perhitungan koefisien pengaruh dan pengujian hipotesis pada
program SIMPLIS
3). Hasil estimasi ukuran pemusatan data masing-masing variabel seperti mean, simpangan
baku berikut histogramnya didisplaykan dengan cukup jelas.
2. Aplikasi Menu SIMPLIS Project
Untuk menguji contoh hipotesis penelitian di atas, buka menu SIMPLIS pada editor
LISREL dengan langkah sebagai berikut:
Klik File
Klik New
Klik SIMPLIS Project
Klik OK
Pada dialog box Save As pilih drive D:
Ketikkan Nama File (misal MARKET.SPJ)
Klik Save
Ketikkan program, mengikuti langkah-langkah seperti yang sudah dijelaskan pada bab 6
sebagai berikut:
Gambar 7.12 Pemrograman SIMPLIS Project
Untuk menjalankan program SIMPLIS Klik File kemudian Klik Run. Maka LISREL
akan mencetak output lengkap sesuai dengan request yang kita inginkan, seperti di bawah
ini:
DATE: 3/ 4/2012
TIME: 21:34
LISREL 8.80 (STUDENT EDITION)
Karl G. Jöreskog & Dag Sörbom
This program is published exclusively by
Scientific Software International, Inc.
7383 N. Lincoln Avenue, Suite 100
Chicago, IL 60646-1704, U.S.A.
Phone: (800)247-6113, (847)675-0720, Fax: (847)675-2140
Copyright by Scientific Software International, Inc., 1981-99
Use of this program is subject to the terms specified in the
Universal Copyright Convention.
Website: www.ssicentral.com
The following lines were read from file D:\MARKET.SPJ:
studi marketing
OBSERVED VARIABLES: X1 X2 X3 X4 X5 X6 X7 X8
correlation matrix
1.000
0.580
1.000
0.556
0.668
1.000
0.542
0.627
0.722
1.000
0.861
0.456
0.369
0.387
1.000
0.458
0.444
0.415
0.850
0.562
0.505
0.556
0.879
0.595
0.510
0.619
0.864
0.448
1.000
0.357
0.588
1.000
0.400
0.560
0.588
1.000
Relationships
X5 = X2 X4 X7
X6 = X3 X5 X7
X7 = X1 X3 X4
X8 = X1 X2 X4 X7
sample size 124
Options RS EF SC SS Nd=5
Path Diagram
End of problem
Sample Size =
124
studi marketing
Correlation Matrix to be Analyzed
X5
X6
X7
X8
X1
X2
X3
X4
X5
-------1.00000
0.44800
0.35700
0.40000
0.86100
0.45600
0.36900
0.38700
X6
--------
X7
--------
X8
--------
X1
--------
X2
--------
1.00000
0.58800
0.56000
0.45800
0.85000
0.55600
0.51000
1.00000
0.58800
0.44400
0.56200
0.87900
0.61900
1.00000
0.41500
0.50500
0.59500
0.86400
1.00000
0.58000
0.55600
0.54200
1.00000
0.66800
0.62700
Correlation Matrix to be Analyzed
X3
X4
X3
-------1.00000
0.72200
STUDI MARKETING
Number of Iterations =
X4
-------1.00000
5
LISREL Estimates (Maximum Likelihood)
X5 = 0.099319*X7 + 0.32310*X2 + 0.12294*X4, Errorvar.= 0.76963 , R² = 0.23087
(0.10737)
(0.10825)
(0.11304)
(0.099776)
0.92502
2.98481
1.08760
7.71362
X6 = 0.26605*X5 + 0.39844*X7 + 0.10759*X3, Errorvar.= 0.58670 , R² = 0.41450
(0.076341)
(0.14735)
(0.14941)
(0.076060)
3.48507
2.70399
0.72015
7.71362
X7 =
- 0.061781*X1 + 0.92384*X3 - 0.014525*X4, Errorvar.= 0.22437 , R² = 0.77563
(0.053875)
(0.065437)
(0.064721)
(0.029087)
-1.14674
14.11793
-0.22443
7.71362
X8 = 0.11733*X7 - 0.071024*X1 - 0.066031*X2 + 0.87127*X4, Errorvar.= 0.24105 , R² = 0.7589
(0.060201)
(0.057677)
(0.064355)
(0.065102)
(0.031250)
1.94892
-1.23142
-1.02604
13.38307
7.71362
Correlation Matrix of Independent Variables
X1
-------1.00000
(0.12964)
7.71362
X2
--------
X2
0.58000
(0.10597)
5.47310
1.00000
(0.12964)
7.71362
X3
0.55600
(0.10489)
5.30098
0.66800
(0.11024)
6.05944
1.00000
(0.12964)
7.71362
X4
0.54200
0.62700
0.72200
X1
X3
--------
X4
--------
1.00000
(0.10427)
5.19811
(0.10820)
5.79489
(0.11307)
6.38566
(0.12964)
7.71362
Goodness of Fit Statistics
Degrees of Freedom = 9
Minimum Fit Function Chi-Square = 349.29862 (P = 0.0)
Normal Theory Weighted Least Squares Chi-Square = 204.46422 (P = 0.0)
Estimated Non-centrality Parameter (NCP) = 195.46422
90 Percent Confidence Interval for NCP = (152.60125 ; 245.75765)
Minimum Fit Function Value = 2.83983
Population Discrepancy Function Value (F0) = 1.64256
90 Percent Confidence Interval for F0 = (1.28236 ; 2.06519)
Root Mean Square Error of Approximation (RMSEA) = 0.42721
90 Percent Confidence Interval for RMSEA = (0.37747 ; 0.47903)
P-Value for Test of Close Fit (RMSEA < 0.05) = 0.00000
Expected Cross-Validation Index (ECVI) = 2.17197
90 Percent Confidence Interval for ECVI = (1.81178 ; 2.59460)
ECVI for Saturated Model = 0.60504
ECVI for Independence Model = 8.89990
Chi-Square for Independence Model with 28 Degrees of Freedom = 1043.08831
Independence AIC = 1059.08831
Model AIC = 258.46422
Saturated AIC = 72.00000
Independence CAIC = 1089.65056
Model CAIC = 361.61183
Saturated CAIC = 209.53014
Root Mean Square Residual (RMR) = 0.12525
Standardized RMR = 0.12517
Goodness of Fit Index (GFI) = 0.70643
Adjusted Goodness of Fit Index (AGFI) = -0.17430
Parsimony Goodness of Fit Index (PGFI) = 0.17661
Normed Fit Index (NFI) = 0.66513
Non-Normed Fit Index (NNFI) = -0.04297
Parsimony Normed Fit Index (PNFI) = 0.21379
Comparative Fit Index (CFI) = 0.66476
Incremental Fit Index (IFI) = 0.67092
Relative Fit Index (RFI) = -0.04182
Critical N (CN) = 8.62953
Studi Marketing
Fitted Covariance Matrix
X5
X6
X7
X8
X1
X2
X3
X4
X5
-------1.00065
0.45195
0.36029
0.32810
0.29813
0.45701
0.39189
0.38700
X6
--------
X7
--------
X8
--------
X1
--------
X2
--------
1.00205
0.58888
0.39109
0.31605
0.42145
0.56209
0.42728
1.00000
0.58733
0.44400
0.57218
0.87900
0.61900
0.99984
0.41500
0.50619
0.64859
0.86400
1.00000
0.58000
0.55600
0.54200
1.00000
0.66800
0.62700
X6
--------
X7
--------
X8
--------
X1
--------
X2
--------
-0.00205
-0.00088
- -
Fitted Covariance Matrix
X3
X4
X3
-------1.00000
0.72200
X4
-------1.00000
Fitted Residuals
X5
X6
X7
X5
--------0.00065
-0.00395
-0.00329
X8
X1
X2
X3
X4
0.07190
0.56287
-0.00101
-0.02289
0.00000
0.16891
0.14195
0.42855
-0.00609
0.08272
0.00067
0.00000
-0.01018
0.00000
0.00000
0.00016
0.00000
-0.00119
-0.05359
0.00000
-
-
0.00000
0.00000
0.00000
X1
--------
X2
--------
Fitted Residuals
X3
X4
X3
-------0.00000
0.00000
X4
-------0.00000
Summary Statistics for Fitted Residuals
Smallest Fitted Residual =
Median Fitted Residual =
Largest Fitted Residual =
-0.05359
0.00000
0.56287
Stemleaf Plot
- 0|521100000000000000000000000000
0|78
1|47
2|
3|
4|3
5|6
Standardized Residuals
X5
X6
X7
X8
X1
X2
X3
X4
X5
--------0.34296
-0.71009
-0.34297
1.80892
8.96932
-0.34294
-0.70611
- -
X6
--------
X7
--------
X8
--------
-0.71970
-0.34297
3.11830
2.36550
8.30929
-0.70611
1.72837
- 0.34293
- -0.34297
- - -
0.34317
- -0.34296
-3.00164
- -
Standardized Residuals
X3
X4
X3
-------- - -
X4
-------- -
Summary Statistics for Standardized Residuals
Smallest Standardized Residual =
Median Standardized Residual =
Largest Standardized Residual =
studi marketing
-3.00164
0.00000
8.96932
-
-
- - - -
Qplot of Standardized Residuals
3.5..........................................................................
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-3.5..........................................................................
-3.5
3.5
Standardized Residuals
The Modification Indices Suggest to Add the
Path to from
Decrease in Chi-Square
New Estimate
X5
X6
65.6
-2.78
X6
X8
8.6
0.27
X7
X8
9.1
0.34
X8
X5
8.1
0.15
X8
X6
14.1
0.21
X5
X1
80.4
0.92
X6
X2
74.9
0.85
X8
X3
9.0
-0.34
The Modification Indices Suggest to Add an Error Covariance
Between
and
Decrease in Chi-Square
New Estimate
X6
X5
65.7
-1.66
X8
X5
8.1
0.11
X8
X6
10.4
0.11
X8
X7
9.0
0.08
X5
X5
65.7
6.25
X6
X8
X1
X1
X2
X2
X2
X2
X3
X3
X3
X4
X4
X5
X6
X5
X8
X5
X6
X1
X2
X6
X7
X8
X1
X3
65.7
10.4
97.2
9.0
100.6
85.6
71.2
35.5
20.8
17.5
10.1
49.3
10.6
-1.66
0.11
0.58
0.58
-1.08
0.43
-1.47
2.48
-0.24
0.26
-0.06
-1.64
0.07
studi marketing
Standardized Solution
BETA
X5
X6
X7
X8
X5
-------- 0.26587
- - -
X6
-------- - - - -
X7
-------0.09929
0.39803
- 0.11734
X8
-------- - - - -
X2
-------0.32300
- - -0.06604
X3
-------- 0.10748
0.92384
- -
X4
-------0.12290
- -0.01453
0.87134
GAMMA
X5
X6
X7
X8
X1
-------- - -0.06178
-0.07103
Correlation Matrix of Y and X
X5
X6
X7
X8
X1
X2
X3
X4
X5
-------1.00000
0.45134
0.36017
0.32802
0.29803
0.45686
0.39177
0.38687
X6
--------
X7
--------
X8
--------
X1
--------
X2
--------
1.00000
0.58827
0.39072
0.31573
0.42101
0.56151
0.42684
1.00000
0.58737
0.44400
0.57218
0.87900
0.61900
1.00000
0.41503
0.50623
0.64864
0.86407
1.00000
0.58000
0.55600
0.54200
1.00000
0.66800
0.62700
Correlation Matrix of Y and X
X3
X4
X3
-------1.00000
0.72200
X4
-------1.00000
PSI
Note: This matrix is diagonal.
X5
-------0.76913
X6
-------0.58550
X7
-------0.22437
X8
-------0.24109
Regression Matrix Y on X (Standardized)
X1
X2
X3
X4
----------------------------X5
-0.00613
0.32300
0.09172
0.12145
X6
-0.02622
0.08587
0.49959
0.02651
X7
-0.06178
- 0.92384
-0.01453
X8
-0.07828
-0.06604
0.10840
0.86964
Studi Marketing
Total and Indirect Effects
Total Effects of X on Y
X1
--------0.00614
(0.00852)
-0.71998
X2
-------0.32310
(0.10825)
2.98481
X3
-------0.09175
(0.09941)
0.92304
X4
-------0.12149
(0.11386)
1.06704
X6
-0.02625
(0.02470)
-1.06291
0.08596
(0.03792)
2.26701
0.50010
(0.08354)
5.98626
0.02654
(0.04199)
0.63201
X7
-0.06178
(0.05388)
-1.14674
- -
0.92384
(0.06544)
14.11793
-0.01453
(0.06472)
-0.22443
X8
-0.07827
(0.05837)
-1.34108
-0.06603
(0.06435)
-1.02604
0.10839
(0.05614)
1.93061
0.86957
(0.06588)
13.19936
X5
Indirect Effects of X on Y
X1
--------0.00614
(0.00852)
-0.71998
X2
-------- -
X3
-------0.09175
(0.09941)
0.92304
X4
--------0.00144
(0.00661)
-0.21810
X6
-0.02625
(0.02470)
-1.06291
0.08596
(0.03792)
2.26701
0.39251
(0.14136)
2.77675
0.02654
(0.04199)
0.63201
X7
- -
- -
- -
- -
X8
-0.00725
(0.00733)
-0.98835
- -
0.10839
(0.05614)
1.93061
-0.00170
(0.00764)
-0.22296
X6
-------- -
X7
-------0.09932
(0.10737)
0.92502
X8
-------- -
X5
Total Effects of Y on Y
X5
X5
-------- -
X6
0.26605
(0.07634)
3.48507
- -
0.42487
(0.15002)
2.83207
- -
X7
- -
- -
- -
- -
X8
- -
- -
0.11733
(0.06020)
1.94892
- -
Largest Eigenvalue of B*B' (Stability Index) is
0.246
Indirect Effects of Y on Y
X5
X5
-------- -
X6
-------- -
X7
-------- -
X8
-------- -
X6
- -
- -
0.02642
(0.02956)
0.89406
- -
X7
- -
- -
- -
- -
X8
- -
- -
- -
- -
Standardized Total and Indirect Effects
Standardized Total Effects of X on Y
X5
X6
X7
X8
X1
--------0.00613
-0.02622
-0.06178
-0.07828
X2
-------0.32300
0.08587
- -0.06604
X3
-------0.09172
0.49959
0.92384
0.10840
X4
-------0.12145
0.02651
-0.01453
0.86964
Standardized Indirect Effects of X on Y
X5
X6
X7
X8
X1
--------0.00613
-0.02622
- -0.00725
X2
-------- 0.08587
- - -
X3
-------0.09172
0.39211
- 0.10840
X4
--------0.00144
0.02651
- -0.00170
Standardized Total Effects of Y on Y
X5
X6
X7
X8
X5
-------- 0.26587
- - -
X6
-------- - - - -
X7
-------0.09929
0.42443
- 0.11734
X8
-------- - - - -
Standardized Indirect Effects of Y on Y
X5
X6
X7
X8
X5
-------- - - - -
X6
-------- - - - -
The Problem used
X7
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UNTUK LEBIH JELASNYA, PEMBAHASAN DAN INTERPRETASI OUTPUT LISREL
DI ATAS DAPAT DILIHAT PADA BUKU APLIKASI LISREL UNTUK PENELITIAN
ANALISIS JALUR PENERBIT ANDI PUBLISHER YOGYAKARTA 2013
AUTHOR: DR. EDI RIADI
HUBUNGI TOKO BUKU GRAMEDIA, GUNUNG AGUNG TERDEKAT
ATAU TOKO BUKU ONLINE FAVORIT ANDA
PENGARUH BAURAN PEMASARAN (MIX MARKETING) TERHADAP EKUITAS
MERK (BRANDING EQUITY)
STUDI ANALISIS JALUR DENGAN LISREL
Processm
X5
Sponsorship
X1
r25
r56
r12
Brand
X6
r75
Promotion
X2
r13
e1
r17
e2
r36
r76
r14
r23
r18
Pricing
X3
r24
r37
Public Rel
X7
e3
r28
r34
r45
r78
r47
Power
X4
r48
Place
X8
e4
Gambar 7.7 The 8-factor path analysis of the marketing mix
Contoh hipotesis yang diajukan
a.
Terdapat pengaruh langsung positif sponsorship terhadap public relation
management
b.
Terdapat pengaruh langsung positif sponsorship terhadap placement management
c.
Terdapat pengaruh langsung positif promotion management terhadap management
process
d.
Terdapat pengaruh langsung positif management promotion terhadap placement
management
e.
Terdapat pengaruh langsung positif pricing management terhadap brand
mangement
f.
Terdapat pengaruh langsung positif pricing management terhadap public relation
management
g.
Terdapat pengaruh langsung positif power of the market terhadap management
process
h.
Terdapat pengaruh langsung positif power of the market terhadap public relation
management
i.
Terdapat pengaruh langsung positif power of the market terhadap placement
management
j.
Terdapat pengaruh langsung positif management process terhadap brand
management
k.
Terdapat pengaruh langsung positif public relation management terhadap brand
management
l.
Terdapat pengaruh langsung positif public relation management terhadap
management process
m.
Terdapat pengaruh langsung positif public relation management terhadap placement
management
n.
Terdapat pengaruh tidak langsung sponsorship terhadap management process
melalui public relation management
o.
Terdapat pengaruh tidak langsung sponsorship terhadap brand management
melalui public relation mangement
p.
Terdapat pengaruh tidak langsung positif sponsorship terhadap place management
melalui public relation mangement
q.
Terdapat pengaruh tidak langsung positif promotion management terhadap brand
management melalui process mangement
r.
Hipotesis pertama: Terdapat pengaruh tidak langsung positif pricing management
terhadap process management melalui public relation mangement
s.
Terdapat pengaruh tidak langsung positif pricing management terhadap brand
management melalui public relation mangement
t.
Terdapat pengaruh tidak langsung positif pricing management terhadap place
management melalui public relation mangement
u.
Terdapat pengaruh tidak langsung positif power of market management terhadap
process management melalui public relation mangement
v.
Terdapat pengaruh tidak langsung positif power of market management terhadap
brand management melalui public relation mangement dan process management
w.
Terdapat pengaruh tidak langsung positif power of market management terhadap
place management melalui public relation mangement
x.
Terdapat pengaruh tidak langsung public relation management terhadap brand
management melalui process mangement
1. Siapkan Menu PRELIS Data
1.1 Input data
Untuk menguji contoh hipotesis penelitian di atas, buka menu PRELIS Data pada editor
LISREL kemudian ikuti langkah sebagai berikut:
Klik File
Klik New
Klik PRELIS Data
Klik OK
Klik Data
Klik Define variabel
Klik Insert
Pada dialog box Add variables ketik X1-X8
Klik OK
Pada dialog box define variabel sudah terisi X1 X2 X3 X4 X5 X6 X7 X8 selanjutnya klik
OK
Gambar 7.8 Menu PRELIS Data
Klik Data
Klik Insert cases
Ketikkan jumlah responden yang akan diteliti (misal 124) klik OK
Gambar 7.9 Menu input data PRELIS
Terlihat editor PRELIS Data LISREL yang sudah siap diinput, Klik sel yang akan diisi
data sekali lagi data ini hanya untuk ilustrasi saja bukan hasil penelitian yang sebenarnya,
setelah itu input contoh data berikut:
Tabel 7.3 Contoh Data Penelitian
RESP
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
X1
186
159
220
144
163
153
218
197
173
177
188
157
183
224
158
129
148
142
196
166
184
137
145
162
164
217
171
195
176
201
169
162
170
183
X2
113
72
162
105
121
96
157
136
103
104
129
110
127
163
122
95
118
124
135
100
66
96
114
124
106
152
59
135
115
140
101
91
118
112
X3
119
98
154
61
84
117
152
137
69
114
129
105
126
158
85
72
115
123
135
116
111
115
118
82
117
152
89
135
104
139
107
101
110
98
X4
110
92
155
61
87
88
150
128
99
107
118
102
114
156
96
102
94
112
127
73
87
44
109
100
101
145
107
127
76
134
93
97
73
43
X5
164
188
178
225
202
149
193
158
223
191
229
163
182
168
162
134
153
147
201
171
189
142
150
167
169
222
176
200
181
206
174
167
175
188
X6
124
69
118
102
100
159
93
119
154
160
107
133
126
110
101
92
115
121
132
97
63
93
111
121
103
149
56
132
112
137
98
88
115
109
X7
90
132
125
104
75
120
135
158
91
164
67
143
160
111
123
78
121
129
141
122
117
121
124
88
123
158
95
141
110
145
113
107
116
104
X8
109
102
145
113
123
151
94
105
91
150
83
82
56
97
87
97
89
107
122
68
82
39
104
95
96
140
102
122
71
129
88
92
68
38
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
168
197
178
204
214
167
229
176
181
195
136
161
163
138
211
176
175
192
171
170
143
190
174
193
184
185
169
181
136
174
177
209
141
185
179
198
179
175
143
167
178
185
131
175
148
230
127
181
142
149
158
158
202
168
159
110
137
95
143
151
116
166
103
103
134
83
64
98
113
150
120
110
133
119
111
106
128
67
133
99
77
57
120
106
114
121
144
105
101
113
139
112
130
104
125
106
94
97
119
100
164
70
80
126
113
107
115
141
124
96
71
137
99
142
149
100
164
120
84
134
108
93
113
66
148
78
91
132
114
86
76
127
100
132
122
107
71
109
108
86
88
145
116
92
121
138
64
131
83
125
111
67
94
121
119
166
97
106
125
74
85
101
140
124
65
42
129
90
136
145
105
158
110
53
126
79
108
72
58
144
97
90
120
104
106
91
116
79
122
112
86
95
89
103
54
91
142
58
79
111
129
103
119
90
113
85
79
95
111
110
159
89
91
114
106
89
84
134
113
94
173
202
183
209
219
172
234
181
186
200
141
166
168
143
216
181
180
197
176
175
148
195
179
198
189
190
174
186
141
179
182
214
146
190
184
203
184
180
148
172
183
190
136
180
153
235
132
186
147
154
163
163
207
173
164
107
134
92
140
148
113
163
100
100
131
80
61
95
110
147
117
107
130
116
108
103
125
64
130
96
74
54
117
103
111
118
141
102
98
110
136
109
127
101
122
103
91
94
116
97
161
67
77
123
110
104
112
138
121
93
77
143
105
148
155
106
170
126
90
140
114
99
119
72
154
84
97
138
120
92
82
133
106
138
128
113
77
115
114
92
94
151
122
98
127
144
70
137
89
131
117
73
100
127
125
172
103
112
131
80
91
107
146
130
71
37
124
85
131
140
100
153
105
48
121
74
103
67
53
139
92
85
115
99
101
86
111
74
117
107
81
90
84
98
49
86
137
53
74
106
124
98
114
85
108
80
74
90
106
105
154
84
86
109
101
84
79
129
108
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
173
149
180
146
160
113
180
146
208
150
145
166
212
182
125
160
210
134
122
194
143
157
182
189
144
184
161
190
150
172
186
165
164
172
132
87
98
108
79
72
125
112
107
143
60
101
107
150
76
102
102
148
121
90
134
113
84
91
99
78
109
67
132
94
123
108
108
111
93
128
112
102
113
95
91
124
76
88
143
98
109
110
148
87
120
60
146
115
77
133
94
110
63
93
102
112
77
131
123
104
103
83
118
90
128
99
104
100
86
65
113
74
68
138
105
60
101
144
75
111
62
143
88
96
124
105
94
106
78
97
65
81
120
112
73
51
88
109
108
117
178
154
185
151
165
118
185
151
213
155
150
171
217
187
130
165
215
139
127
199
148
162
187
194
149
189
166
195
155
177
191
170
169
177
137
84
95
105
76
69
122
109
104
140
57
98
104
147
73
99
99
145
118
87
131
110
81
88
96
75
106
64
129
91
120
105
105
108
90
125
118
108
119
101
97
130
82
94
149
104
115
116
154
93
126
66
152
121
83
139
100
116
69
99
108
118
83
137
129
110
109
89
124
96
134
94
99
95
81
60
108
69
63
133
100
55
96
139
70
106
57
138
83
91
119
100
89
101
73
92
60
76
115
107
68
46
83
104
103
112
Setelah selesai menginput data, simpan terlebih dahulu raw data tersebut misalnya di drive D:
dengan nama file: MARKET.PSF, caranya klik File, klik Save As, pada dialog box File Save As,
klik D: pada kotak Drives kemudian klik pada kotak File name lalu ketikkan MARKET.PSF
akhiri dengan mengklik OK. Sebaliknya untuk membuka file yang sudah tersimpan, Klik File,
klik Open, pada kotak Drives: pilih D, pada kotak Save file as type pilih all files (*.*), pada
kotak File name tarik slider ke bawah klik MARKET.PSF akhiri dengan OK
Gambar 7.10 Menu Save As PRELIS
1.2 Analisis Deskripsi Data dan Normalitas Data
Setelah file MARKET.PSF terbuka selanjutnya untuk mengetahui deskripsi atau gambaran data
seperti normalitas data baik secara univariat maupun multivariat, histogram masing-masing
variabel, matrik korelasional, rerata (mean), dan simpangan baku antar variabel, dengan mudah
dapat dianalisis melalui menu PRELIS Data LISREL. Namun sebelum dianalisis, definisikan
terlebih dahulu jenis data yang akan dipakai, ini penting karena LISREL akan memperlakukan
variabel kategorikal yang terdistribusi secara normal dapat dianggap sebagai jenis data kontinyu.
Untuk itu ikuti langkah-langkah sebagai berikut:
Klik Data, pada editor PRELIS
Klik Define Variables
Pada kotak Define variables sudah berisi variabel X1 sd X8
Dengan menekan Ctrl (jangan dilepas) lalu klik X1 sd X8 terlihat berwarna biru
Lepas Ctrl, lalu klik Variable Type
Tampak beberapa pilihan tipe variabel, lalu klik Continous, klik OK
Setelah tipe variabel ditentukan langkah berikutnya menganalisis estimasi deskripsi masingmasing variabel menggunakan menu statistik pada PRELIS LISREL. Langkah-langkahnya
sebagai berikut:
Klik menu Statistics
Terlihat beberapa pilihan, untuk kali ini klik Output Option
Gambar 7.11 Menu Output Option PRELIS
Klik kotak pada LISREL system data
Klik kotak di bawah Moment Matrix pilh Correlations,
klik kotak Save the transformed data to file,
lalu ketikkan nama File misalnya DESKRIP,
klik kotak pada Perform tests of multivariate normality, yang lainnya abaikan,
akhiri dengan klik OK
Hasil output LISREL dapat dilihat sebagai berikut:
DATE: 03/04/2012
TIME: 19:09
LISREL 8.80 (STUDENT EDITION)
BY
Karl G. Jöreskog & Dag Sörbom
This program is published exclusively by
Scientific Software International, Inc.
7383 N. Lincoln Avenue, Suite 100
Chicago, IL 60646-1704, U.S.A.
Phone: (800)247-6113, (847)675-0720, Fax: (847)675-2140
Copyright by Scientific Software International, Inc., 1981-99
Use of this program is subject to the terms specified in the
Universal Copyright Convention.
Website: www.ssicentral.com
The following lines were read from file D:\MARKET.PR2:
!PRELIS SYNTAX: Can be edited
SY=D:\MARKET.PSF
OU MA=KM RA=MARKET.PR2 ME= SD= DESKRIP
Total Sample Size =
124
Univariate Summary Statistics for Continuous Variables
Variable
-------X1
X2
X3
X4
X5
X6
X7
X8
Mean
---171.274
111.234
108.790
100.597
176.274
108.234
114.790
95.597
St. Dev.
-------24.457
23.721
24.622
25.621
24.457
23.721
24.622
25.621
T-Value
------77.982
52.217
49.201
43.721
80.259
50.809
51.914
41.548
Skewness
-------0.125
-0.011
0.056
0.045
0.125
-0.011
0.056
0.045
Kurtosis
--------0.311
-0.110
-0.613
-0.127
-0.311
-0.110
-0.613
-0.127
Minimum Freq.
------- ----113.000
1
57.000
1
60.000
1
42.000
1
118.000
1
54.000
1
66.000
1
37.000
1
Maximum Freq.
------- ----230.000
1
166.000
1
166.000
1
159.000
1
235.000
1
163.000
1
172.000
1
154.000
1
Test of Univariate Normality for Continuous Variables
Skewness
Variable Z-Score P-Value
X1
X2
X3
X4
X5
X6
X7
X8
0.573
-0.052
0.255
0.207
0.573
-0.052
0.255
0.207
Kurtosis
Skewness and Kurtosis
Z-Score P-Value
0.566
0.958
0.799
0.836
0.566
0.958
0.799
0.836
-0.564
0.017
-1.714
-0.029
-0.564
0.017
-1.714
-0.029
Chi-Square P-Value
0.573
0.986
0.087
0.977
0.573
0.986
0.087
0.977
0.647
0.003
3.002
0.044
0.647
0.003
3.002
0.044
0.724
0.998
0.223
0.978
0.724
0.998
0.223
0.978
Relative Multivariate Kurtosis = 2.538
Test of Multivariate Normality for Continuous Variables
Skewness
Value
-----63.623
Z-Score P-Value
------- ------28.419
0.000
Kurtosis
Value
------124.317
Skewness and Kurtosis
Z-Score P-Value
------- ------13.037
0.000
Chi-Square P-Value
---------- ------977.577
0.000
Histograms for Continuous Variables
X1
Frequency Percentage Lower Class Limit
2
1.6
113.000
••
8
6.5
124.700
••••••••
16
12.9
136.400
••••••••••••••••
12
9.7
148.100
••••••••••••
23
18.5
159.800
•••••••••••••••••••••••
27
21.8
171.500
•••••••••••••••••••••••••••
15
12.1
183.200
•••••••••••••••
9
7.3
194.900
•••••••••
8
6.5
206.600
••••••••
4
3.2
218.300
••••
X2
Frequency Percentage Lower Class Limit
7
5.6
57.000
•••••••
6
4.8
67.900
••••••
5
4.0
78.800
•••••
18
14.5
89.700
••••••••••••••••••
28
22.6
100.600
••••••••••••••••••••••••••••
23
18.5
111.500
•••••••••••••••••••••••
15
12.1
122.400
•••••••••••••••
12
9.7
133.300
••••••••••••
5
4.0
144.200
•••••
5
4.0
155.100
•••••
X3
Frequency Percentage Lower Class Limit
8
6.5
60.000
••••••••
9
7.3
70.600
•••••••••
16
12.9
81.200
••••••••••••••••
17
13.7
91.800
•••••••••••••••••
20
16.1
102.400
••••••••••••••••••••
20
16.1
113.000
••••••••••••••••••••
14
11.3
123.600
••••••••••••••
9
7.3
134.200
•••••••••
8
6.5
144.800
••••••••
3
2.4
155.400
•••
X4
Frequency Percentage Lower Class Limit
5
4.0
42.000
•••••
8
6.5
53.700
••••••••
8
15
25
29
12
9
8
5
6.5
12.1
20.2
23.4
9.7
7.3
6.5
4.0
65.400
77.100
88.800
100.500
112.200
123.900
135.600
147.300
••••••••
•••••••••••••••
•••••••••••••••••••••••••
•••••••••••••••••••••••••••••
••••••••••••
•••••••••
••••••••
•••••
X5
Frequency Percentage Lower Class Limit
2
1.6
118.000
••
8
6.5
129.700
••••••••
16
12.9
141.400
••••••••••••••••
12
9.7
153.100
••••••••••••
23
18.5
164.800
•••••••••••••••••••••••
27
21.8
176.500
•••••••••••••••••••••••••••
15
12.1
188.200
•••••••••••••••
9
7.3
199.900
•••••••••
8
6.5
211.600
••••••••
4
3.2
223.300
••••
X6
Frequency Percentage Lower Class Limit
7
5.6
54.000
•••••••
6
4.8
64.900
••••••
5
4.0
75.800
•••••
18
14.5
86.700
••••••••••••••••••
28
22.6
97.600
••••••••••••••••••••••••••••
23
18.5
108.500
•••••••••••••••••••••••
15
12.1
119.400
•••••••••••••••
12
9.7
130.300
••••••••••••
5
4.0
141.200
•••••
5
4.0
152.100
•••••
X7
Frequency Percentage Lower Class Limit
8
6.5
66.000
••••••••
9
7.3
76.600
•••••••••
16
12.9
87.200
••••••••••••••••
17
13.7
97.800
•••••••••••••••••
20
16.1
108.400
••••••••••••••••••••
20
16.1
119.000
••••••••••••••••••••
14
11.3
129.600
••••••••••••••
9
7.3
140.200
•••••••••
8
6.5
150.800
••••••••
3
2.4
161.400
•••
X8
Frequency Percentage Lower Class Limit
5
4.0
37.000
•••••
8
6.5
48.700
••••••••
8
6.5
60.400
••••••••
15
12.1
72.100
•••••••••••••••
25
20.2
83.800
•••••••••••••••••••••••••
29
23.4
95.500
•••••••••••••••••••••••••••••
12
9.7
107.200
••••••••••••
9
7.3
118.900
•••••••••
8
6.5
130.600
••••••••
5
4.0
142.300
•••••
Correlation Matrix
X1
X2
X3
X4
X5
X6
X7
X8
X1
-------1.000
0.580
0.556
0.542
0.861
0.458
0.444
0.415
Correlation Matrix
X2
--------
X3
--------
X4
--------
X5
--------
X6
--------
1.000
0.668
0.627
0.456
0.850
0.562
0.505
1.000
0.722
0.369
0.556
0.879
0.595
1.000
0.387
0.510
0.619
0.864
1.000
0.448
0.357
0.400
1.000
0.588
0.560
X7
X8
X7
-------1.000
0.588
X8
--------
X1
-------171.274
X2
-------111.234
X7
-------114.790
X8
-------95.597
1.000
Means
X3
-------108.790
X4
-------100.597
X5
-------176.274
X6
-------108.234
X3
-------24.622
X4
-------25.621
X5
-------24.457
X6
-------23.721
Means
Standard Deviations
X1
-------24.457
X2
-------23.721
Standard Deviations
X7
-------24.622
X8
-------25.621
The Problem used
9496 Bytes (= 0.0% of available workspace)
1.3 Diskusi Statistik Deskripsi dan Normalitas Data
1). Hasil uji normalitas univariat variabel X1, X2, X3, X4, X5, X6, X7 dan X8, diperoleh
Zskewness dan Zkurtosis berada diantara -1.96 hingga +1,96. Sebagai contoh kita ambil variabel
X1 Zskewness = 0,566 dan Zkurtosis = -0.564 Dengan demikian nilai Zskewness dan Zkurtosis untuk
variabel X1 berada diantara -1,96 hingga +1,96 sehingga dapat disimpulkan bahwa data
variabel X1 cenderung berdistribusi normal. Demikian juga nilai Pskewness maupun Pkurtosis
untuk variabel berturut-turut 0.566 dan 0.573 lebih besar dari α = 0,05 sehingga dapat
disimpulkan bahwa data variabel X1 cenderung berdistribusi normal.
2). Matrik koefisien korelasi antar variabel semuanya bernilai positif sehingga dapat dilanjutkan
sebagai data input untuk perhitungan koefisien pengaruh dan pengujian hipotesis pada
program SIMPLIS
3). Hasil estimasi ukuran pemusatan data masing-masing variabel seperti mean, simpangan
baku berikut histogramnya didisplaykan dengan cukup jelas.
2. Aplikasi Menu SIMPLIS Project
Untuk menguji contoh hipotesis penelitian di atas, buka menu SIMPLIS pada editor
LISREL dengan langkah sebagai berikut:
Klik File
Klik New
Klik SIMPLIS Project
Klik OK
Pada dialog box Save As pilih drive D:
Ketikkan Nama File (misal MARKET.SPJ)
Klik Save
Ketikkan program, mengikuti langkah-langkah seperti yang sudah dijelaskan pada bab 6
sebagai berikut:
Gambar 7.12 Pemrograman SIMPLIS Project
Untuk menjalankan program SIMPLIS Klik File kemudian Klik Run. Maka LISREL
akan mencetak output lengkap sesuai dengan request yang kita inginkan, seperti di bawah
ini:
DATE: 3/ 4/2012
TIME: 21:34
LISREL 8.80 (STUDENT EDITION)
Karl G. Jöreskog & Dag Sörbom
This program is published exclusively by
Scientific Software International, Inc.
7383 N. Lincoln Avenue, Suite 100
Chicago, IL 60646-1704, U.S.A.
Phone: (800)247-6113, (847)675-0720, Fax: (847)675-2140
Copyright by Scientific Software International, Inc., 1981-99
Use of this program is subject to the terms specified in the
Universal Copyright Convention.
Website: www.ssicentral.com
The following lines were read from file D:\MARKET.SPJ:
studi marketing
OBSERVED VARIABLES: X1 X2 X3 X4 X5 X6 X7 X8
correlation matrix
1.000
0.580
1.000
0.556
0.668
1.000
0.542
0.627
0.722
1.000
0.861
0.456
0.369
0.387
1.000
0.458
0.444
0.415
0.850
0.562
0.505
0.556
0.879
0.595
0.510
0.619
0.864
0.448
1.000
0.357
0.588
1.000
0.400
0.560
0.588
1.000
Relationships
X5 = X2 X4 X7
X6 = X3 X5 X7
X7 = X1 X3 X4
X8 = X1 X2 X4 X7
sample size 124
Options RS EF SC SS Nd=5
Path Diagram
End of problem
Sample Size =
124
studi marketing
Correlation Matrix to be Analyzed
X5
X6
X7
X8
X1
X2
X3
X4
X5
-------1.00000
0.44800
0.35700
0.40000
0.86100
0.45600
0.36900
0.38700
X6
--------
X7
--------
X8
--------
X1
--------
X2
--------
1.00000
0.58800
0.56000
0.45800
0.85000
0.55600
0.51000
1.00000
0.58800
0.44400
0.56200
0.87900
0.61900
1.00000
0.41500
0.50500
0.59500
0.86400
1.00000
0.58000
0.55600
0.54200
1.00000
0.66800
0.62700
Correlation Matrix to be Analyzed
X3
X4
X3
-------1.00000
0.72200
STUDI MARKETING
Number of Iterations =
X4
-------1.00000
5
LISREL Estimates (Maximum Likelihood)
X5 = 0.099319*X7 + 0.32310*X2 + 0.12294*X4, Errorvar.= 0.76963 , R² = 0.23087
(0.10737)
(0.10825)
(0.11304)
(0.099776)
0.92502
2.98481
1.08760
7.71362
X6 = 0.26605*X5 + 0.39844*X7 + 0.10759*X3, Errorvar.= 0.58670 , R² = 0.41450
(0.076341)
(0.14735)
(0.14941)
(0.076060)
3.48507
2.70399
0.72015
7.71362
X7 =
- 0.061781*X1 + 0.92384*X3 - 0.014525*X4, Errorvar.= 0.22437 , R² = 0.77563
(0.053875)
(0.065437)
(0.064721)
(0.029087)
-1.14674
14.11793
-0.22443
7.71362
X8 = 0.11733*X7 - 0.071024*X1 - 0.066031*X2 + 0.87127*X4, Errorvar.= 0.24105 , R² = 0.7589
(0.060201)
(0.057677)
(0.064355)
(0.065102)
(0.031250)
1.94892
-1.23142
-1.02604
13.38307
7.71362
Correlation Matrix of Independent Variables
X1
-------1.00000
(0.12964)
7.71362
X2
--------
X2
0.58000
(0.10597)
5.47310
1.00000
(0.12964)
7.71362
X3
0.55600
(0.10489)
5.30098
0.66800
(0.11024)
6.05944
1.00000
(0.12964)
7.71362
X4
0.54200
0.62700
0.72200
X1
X3
--------
X4
--------
1.00000
(0.10427)
5.19811
(0.10820)
5.79489
(0.11307)
6.38566
(0.12964)
7.71362
Goodness of Fit Statistics
Degrees of Freedom = 9
Minimum Fit Function Chi-Square = 349.29862 (P = 0.0)
Normal Theory Weighted Least Squares Chi-Square = 204.46422 (P = 0.0)
Estimated Non-centrality Parameter (NCP) = 195.46422
90 Percent Confidence Interval for NCP = (152.60125 ; 245.75765)
Minimum Fit Function Value = 2.83983
Population Discrepancy Function Value (F0) = 1.64256
90 Percent Confidence Interval for F0 = (1.28236 ; 2.06519)
Root Mean Square Error of Approximation (RMSEA) = 0.42721
90 Percent Confidence Interval for RMSEA = (0.37747 ; 0.47903)
P-Value for Test of Close Fit (RMSEA < 0.05) = 0.00000
Expected Cross-Validation Index (ECVI) = 2.17197
90 Percent Confidence Interval for ECVI = (1.81178 ; 2.59460)
ECVI for Saturated Model = 0.60504
ECVI for Independence Model = 8.89990
Chi-Square for Independence Model with 28 Degrees of Freedom = 1043.08831
Independence AIC = 1059.08831
Model AIC = 258.46422
Saturated AIC = 72.00000
Independence CAIC = 1089.65056
Model CAIC = 361.61183
Saturated CAIC = 209.53014
Root Mean Square Residual (RMR) = 0.12525
Standardized RMR = 0.12517
Goodness of Fit Index (GFI) = 0.70643
Adjusted Goodness of Fit Index (AGFI) = -0.17430
Parsimony Goodness of Fit Index (PGFI) = 0.17661
Normed Fit Index (NFI) = 0.66513
Non-Normed Fit Index (NNFI) = -0.04297
Parsimony Normed Fit Index (PNFI) = 0.21379
Comparative Fit Index (CFI) = 0.66476
Incremental Fit Index (IFI) = 0.67092
Relative Fit Index (RFI) = -0.04182
Critical N (CN) = 8.62953
Studi Marketing
Fitted Covariance Matrix
X5
X6
X7
X8
X1
X2
X3
X4
X5
-------1.00065
0.45195
0.36029
0.32810
0.29813
0.45701
0.39189
0.38700
X6
--------
X7
--------
X8
--------
X1
--------
X2
--------
1.00205
0.58888
0.39109
0.31605
0.42145
0.56209
0.42728
1.00000
0.58733
0.44400
0.57218
0.87900
0.61900
0.99984
0.41500
0.50619
0.64859
0.86400
1.00000
0.58000
0.55600
0.54200
1.00000
0.66800
0.62700
X6
--------
X7
--------
X8
--------
X1
--------
X2
--------
-0.00205
-0.00088
- -
Fitted Covariance Matrix
X3
X4
X3
-------1.00000
0.72200
X4
-------1.00000
Fitted Residuals
X5
X6
X7
X5
--------0.00065
-0.00395
-0.00329
X8
X1
X2
X3
X4
0.07190
0.56287
-0.00101
-0.02289
0.00000
0.16891
0.14195
0.42855
-0.00609
0.08272
0.00067
0.00000
-0.01018
0.00000
0.00000
0.00016
0.00000
-0.00119
-0.05359
0.00000
-
-
0.00000
0.00000
0.00000
X1
--------
X2
--------
Fitted Residuals
X3
X4
X3
-------0.00000
0.00000
X4
-------0.00000
Summary Statistics for Fitted Residuals
Smallest Fitted Residual =
Median Fitted Residual =
Largest Fitted Residual =
-0.05359
0.00000
0.56287
Stemleaf Plot
- 0|521100000000000000000000000000
0|78
1|47
2|
3|
4|3
5|6
Standardized Residuals
X5
X6
X7
X8
X1
X2
X3
X4
X5
--------0.34296
-0.71009
-0.34297
1.80892
8.96932
-0.34294
-0.70611
- -
X6
--------
X7
--------
X8
--------
-0.71970
-0.34297
3.11830
2.36550
8.30929
-0.70611
1.72837
- 0.34293
- -0.34297
- - -
0.34317
- -0.34296
-3.00164
- -
Standardized Residuals
X3
X4
X3
-------- - -
X4
-------- -
Summary Statistics for Standardized Residuals
Smallest Standardized Residual =
Median Standardized Residual =
Largest Standardized Residual =
studi marketing
-3.00164
0.00000
8.96932
-
-
- - - -
Qplot of Standardized Residuals
3.5..........................................................................
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-3.5..........................................................................
-3.5
3.5
Standardized Residuals
The Modification Indices Suggest to Add the
Path to from
Decrease in Chi-Square
New Estimate
X5
X6
65.6
-2.78
X6
X8
8.6
0.27
X7
X8
9.1
0.34
X8
X5
8.1
0.15
X8
X6
14.1
0.21
X5
X1
80.4
0.92
X6
X2
74.9
0.85
X8
X3
9.0
-0.34
The Modification Indices Suggest to Add an Error Covariance
Between
and
Decrease in Chi-Square
New Estimate
X6
X5
65.7
-1.66
X8
X5
8.1
0.11
X8
X6
10.4
0.11
X8
X7
9.0
0.08
X5
X5
65.7
6.25
X6
X8
X1
X1
X2
X2
X2
X2
X3
X3
X3
X4
X4
X5
X6
X5
X8
X5
X6
X1
X2
X6
X7
X8
X1
X3
65.7
10.4
97.2
9.0
100.6
85.6
71.2
35.5
20.8
17.5
10.1
49.3
10.6
-1.66
0.11
0.58
0.58
-1.08
0.43
-1.47
2.48
-0.24
0.26
-0.06
-1.64
0.07
studi marketing
Standardized Solution
BETA
X5
X6
X7
X8
X5
-------- 0.26587
- - -
X6
-------- - - - -
X7
-------0.09929
0.39803
- 0.11734
X8
-------- - - - -
X2
-------0.32300
- - -0.06604
X3
-------- 0.10748
0.92384
- -
X4
-------0.12290
- -0.01453
0.87134
GAMMA
X5
X6
X7
X8
X1
-------- - -0.06178
-0.07103
Correlation Matrix of Y and X
X5
X6
X7
X8
X1
X2
X3
X4
X5
-------1.00000
0.45134
0.36017
0.32802
0.29803
0.45686
0.39177
0.38687
X6
--------
X7
--------
X8
--------
X1
--------
X2
--------
1.00000
0.58827
0.39072
0.31573
0.42101
0.56151
0.42684
1.00000
0.58737
0.44400
0.57218
0.87900
0.61900
1.00000
0.41503
0.50623
0.64864
0.86407
1.00000
0.58000
0.55600
0.54200
1.00000
0.66800
0.62700
Correlation Matrix of Y and X
X3
X4
X3
-------1.00000
0.72200
X4
-------1.00000
PSI
Note: This matrix is diagonal.
X5
-------0.76913
X6
-------0.58550
X7
-------0.22437
X8
-------0.24109
Regression Matrix Y on X (Standardized)
X1
X2
X3
X4
----------------------------X5
-0.00613
0.32300
0.09172
0.12145
X6
-0.02622
0.08587
0.49959
0.02651
X7
-0.06178
- 0.92384
-0.01453
X8
-0.07828
-0.06604
0.10840
0.86964
Studi Marketing
Total and Indirect Effects
Total Effects of X on Y
X1
--------0.00614
(0.00852)
-0.71998
X2
-------0.32310
(0.10825)
2.98481
X3
-------0.09175
(0.09941)
0.92304
X4
-------0.12149
(0.11386)
1.06704
X6
-0.02625
(0.02470)
-1.06291
0.08596
(0.03792)
2.26701
0.50010
(0.08354)
5.98626
0.02654
(0.04199)
0.63201
X7
-0.06178
(0.05388)
-1.14674
- -
0.92384
(0.06544)
14.11793
-0.01453
(0.06472)
-0.22443
X8
-0.07827
(0.05837)
-1.34108
-0.06603
(0.06435)
-1.02604
0.10839
(0.05614)
1.93061
0.86957
(0.06588)
13.19936
X5
Indirect Effects of X on Y
X1
--------0.00614
(0.00852)
-0.71998
X2
-------- -
X3
-------0.09175
(0.09941)
0.92304
X4
--------0.00144
(0.00661)
-0.21810
X6
-0.02625
(0.02470)
-1.06291
0.08596
(0.03792)
2.26701
0.39251
(0.14136)
2.77675
0.02654
(0.04199)
0.63201
X7
- -
- -
- -
- -
X8
-0.00725
(0.00733)
-0.98835
- -
0.10839
(0.05614)
1.93061
-0.00170
(0.00764)
-0.22296
X6
-------- -
X7
-------0.09932
(0.10737)
0.92502
X8
-------- -
X5
Total Effects of Y on Y
X5
X5
-------- -
X6
0.26605
(0.07634)
3.48507
- -
0.42487
(0.15002)
2.83207
- -
X7
- -
- -
- -
- -
X8
- -
- -
0.11733
(0.06020)
1.94892
- -
Largest Eigenvalue of B*B' (Stability Index) is
0.246
Indirect Effects of Y on Y
X5
X5
-------- -
X6
-------- -
X7
-------- -
X8
-------- -
X6
- -
- -
0.02642
(0.02956)
0.89406
- -
X7
- -
- -
- -
- -
X8
- -
- -
- -
- -
Standardized Total and Indirect Effects
Standardized Total Effects of X on Y
X5
X6
X7
X8
X1
--------0.00613
-0.02622
-0.06178
-0.07828
X2
-------0.32300
0.08587
- -0.06604
X3
-------0.09172
0.49959
0.92384
0.10840
X4
-------0.12145
0.02651
-0.01453
0.86964
Standardized Indirect Effects of X on Y
X5
X6
X7
X8
X1
--------0.00613
-0.02622
- -0.00725
X2
-------- 0.08587
- - -
X3
-------0.09172
0.39211
- 0.10840
X4
--------0.00144
0.02651
- -0.00170
Standardized Total Effects of Y on Y
X5
X6
X7
X8
X5
-------- 0.26587
- - -
X6
-------- - - - -
X7
-------0.09929
0.42443
- 0.11734
X8
-------- - - - -
Standardized Indirect Effects of Y on Y
X5
X6
X7
X8
X5
-------- - - - -
X6
-------- - - - -
The Problem used
X7
-------- 0.02640
- - -
20240 Bytes (=
Time used:
X8
-------- - - - 0.0% of Available Workspace)
0.008 Seconds
UNTUK LEBIH JELASNYA, PEMBAHASAN DAN INTERPRETASI OUTPUT LISREL
DI ATAS DAPAT DILIHAT PADA BUKU APLIKASI LISREL UNTUK PENELITIAN
ANALISIS JALUR PENERBIT ANDI PUBLISHER YOGYAKARTA 2013
AUTHOR: DR. EDI RIADI
HUBUNGI TOKO BUKU GRAMEDIA, GUNUNG AGUNG TERDEKAT
ATAU TOKO BUKU ONLINE FAVORIT ANDA