269
Total Variance Explained
Compo nent
Initial Eigenvalues Extraction Sums of Squared Loadings
Total of Variance
Cumulative Total
of Variance Cumulative
1 6.589
50.684 50.684
6.589 50.684
50.684 2
1.536 11.813
62.498 1.536
11.813 62.498
3 1.287
9.897 72.394
1.287 9.897
72.394 4
1.074 8.260
80.654 1.074
8.260 80.654
5 .769
5.916 86.570
6 .610
4.696 91.266
7 .501
3.855 95.121
8 .283
2.175 97.296
9 .240
1.847 99.143
10 .111
.857 100.000
11 1.017E-12
7.819E-12 100.000
12 7.117E-13
5.475E-12 100.000
13 3.739E-13
2.877E-12 100.000
Extraction Method: Principal Component Analysis.
Total Variance Explained
Compo nent
Rotation Sums of Squared Loadings Total
of Variance Cumulative
1 5.422
41.707 41.707
2 1.979
15.223 56.930
3 1.652
12.711 69.640
4 1.432
11.014 80.654
Extraction Method: Principal Component Analysis.
270
Component Matrix
a
Component 1
2 3
4 I1
.844 -.241
.262 -.262
I2 .916
.049 .209
.024 I3
.686 -.399
.348 -.276
I4 .845
.121 .226
.181 I5
.805 .387
-.063 .141
I6 .829
-.016 -.100
.139 I7
.763 -.049
-.362 -.200
I8 .135
-.486 .333
.669 I9
.869 -.110
-.380 -.136
I10 .625
.213 .043
.461 I11
.151 .270
.693 -.362
I12 .205
.872 .050
.048 I13
.841 -.145
-.344 -.065
Extraction Method: Principal Component Analysis.
271
Component Matrix
a
Component 1
2 3
4 I1
.844 -.241
.262 -.262
I2 .916
.049 .209
.024 I3
.686 -.399
.348 -.276
I4 .845
.121 .226
.181 I5
.805 .387
-.063 .141
I6 .829
-.016 -.100
.139 I7
.763 -.049
-.362 -.200
I8 .135
-.486 .333
.669 I9
.869 -.110
-.380 -.136
I10 .625
.213 .043
.461 I11
.151 .270
.693 -.362
I12 .205
.872 .050
.048 I13
.841 -.145
-.344 -.065
Extraction Method: Principal Component Analysis. a. 4 components extracted.
Reproduced Correlations
I1 I2
I3 I4
I5 I6
Reproduced Correlation I1
.908
a
.810 .838
.696 .532
.641 I2
.810 .885
a
.675 .831
.746 .741
I3 .838
.675 .827
a
.560 .337
.502 I4
.696 .831
.560 .812
a
.738 .701
I5 .532
.746 .337
.738 .821
a
.687 I6
.641 .741
.502 .701
.687 .717
a
I7 .613
.616 .472
.521 .589
.641 I8
.143 .185
.218 .252
-.006 .179
I9 .696
.708 .545
.611 .661
.741 I10
.367 .603
.232 .647
.648 .575
I11 .339
.287 .337
.251 .132
.002
272
I12 -.037
.242 -.203
.299 .506
.158 I13
.672 .690
.533 .604
.633 .725
Residual
b
I1 .040
.034 -.026
.026 -.003
I2 .040
-.046 .104
-.059 -.063
I3 .034
-.046 -.008
.045 .004
I4 -.026
.104 -.008
-.096 -.092
I5 .026
-.059 .045
-.096 .202
I6 -.003
-.063 .004
-.092 .202
I7 -.040
-.035 -.067
-.047 -.064
-.081 I8
-.004 -.053
-.030 -.097
.029 -.029
I9 -.041
-.024 -.050
-.019 -.058
-.075 I10
-.052 -.026
-.016 .012
-.151 -.105
I11 -.115
-.084 -.148
-.084 -.031
.021 I12
.063 -.011
.091 -.037
.012 -.088
I13 -.037
-.012 -.030
.007 -.045
-.060 Extraction Method: Principal Component Analysis.
a. Reproduced communalities b. Residuals are computed between observed and reproduced correlations. There are 40 51,0 nonredundant
residuals with absolute values greater than 0.05.
Reproduced Correlations
I7 I8
I9 I10
I11 Reproduced Correlation
I1 .613
.143 .696
.367 .339
I2 .616
.185 .708
.603 .287
I3 .472
.218 .545
.232 .337
I4 .521
.252 .611
.647 .251
I5 .589
-.006 .661
.648 .132
I6 .641
.179 .741
.575 .002
I7 .755
a
-.127 .833
.359 -.076
I8 -.127
.814
a
-.047 .304
-.122 I9
.833 -.047
.930
a
.441 -.112
273
I10 .359
.304 .441
.651
a
.015 I11
-.076 -.122
-.112 .015
.706
a
I12 .086
-.348 .057
.338 .284
I13 .786
.026 .887
.450 -.127
Residual
b
I1 -.040
-.004 -.041
-.052 -.115
I2 -.035
-.053 -.024
-.026 -.084
I3 -.067
-.030 -.050
-.016 -.148
I4 -.047
-.097 -.019
.012 -.084
I5 -.064
.029 -.058
-.151 -.031
I6 -.081
-.029 -.075
-.105 .021
I7 .113
.077 .061
.134 I8
.113 .071
-.123 .084
I9 .077
.071 .036
.106 I10
.061 -.123
.036 .106
I11 .134
.084 .106
.106 I12
.012 .116
.014 -.133
-.107 I13
-.070 .027
.054 .011
.070 Extraction Method: Principal Component Analysis.
a. Reproduced communalities b. Residuals are computed between observed and reproduced correlations. There are 40 51,0
nonredundant residuals with absolute values greater than 0.05.
Reproduced Correlations
I12 I13
Reproduced Correlation I1
-.037 .672
I2 .242
.690 I3
-.203 .533
I4 .299
.604 I5
.506 .633
I6 .158
.725 I7
.086 .786
274
I8 -.348
.026 I9
.057 .887
I10 .338
.450 I11
.284 -.127
I12 .808
a
.026 I13
.026 .851
a
Residual
b
I1 .063
-.037 I2
-.011 -.012
I3 .091
-.030 I4
-.037 .007
I5 .012
-.045 I6
-.088 -.060
I7 .012
-.070 I8
.116 .027
I9 .014
.054 I10
-.133 .011
I11 -.107
.070 I12
.013 I13
.013 Extraction Method: Principal Component Analysis.
a. Reproduced communalities b. Residuals are computed between observed and reproduced
correlations. There are 40 51,0 nonredundant residuals with absolute values greater than 0.05.
275
Rotated Component Matrix
a
Component 1
2 3
4 I1
.742 -.020
.571 .175
I2 .714
.357 .421
.265 I3
.606 -.206
.601 .234
I4 .603
.457 .344
.348 I5
.626 .639
.116 .081
I6 .749
.294 .082
.249 I7
.856 .098
.000 -.114
I8 -.017
-.105 -.005
.896 I9
.959 .101
-.017 -.022
I10 .410
.558 .002
.413 I11
-.127 .199
.799 -.111
I12 -.035
.845 .099
-.289 I13
.916 .091
-.028 .057
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 7 iterations.
Component Transformation Matrix
Compo nent
1 2
3 4
1 .883
.317 .279
.207 2
-.216 .869
.026 -.445
3 -.381
.074 .841
.378 4
-.172 .373
-.464 .785
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.
276
277
II. OUTPUT ANALISIS FAKTOR-FAKTOR EKSTERNAL
Notes
Output Created 07-Aug-2011 10:48:58
Comments Input
Active Dataset DataSet0
Filter none
Weight none
Split File none
N of Rows in Working Data File
114 Missing Value Handling
Definition of Missing MISSING=EXCLUDE: User-defined
missing values are treated as missing. Cases Used
LISTWISE: Statistics are based on cases with no missing values for any
variable used. Syntax
FACTOR VARIABLES I1 I2 I3 I4 I5 I6 I7 I8 I9
I10 MISSING LISTWISE
ANALYSIS I1 I2 I3 I4 I5 I6 I7 I8 I9 I10 PRINT INITIAL KMO AIC
EXTRACTION ROTATION PLOT EIGEN ROTATION
CRITERIA MINEIGEN1 ITERATE25
EXTRACTION PC CRITERIA ITERATE25
ROTATION VARIMAX METHOD=CORRELATION.
Resources Processor Time
00:00:00.969 Elapsed Time
00:00:01.173 Maximum Memory Required
13480 13,164K bytes
278
KMO and Bartletts Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .822
Bartletts Test of Sphericity Approx. Chi-Square
614.291 df
45 Sig.
.000
Anti-image Matrices
I1 I2
I3 I4
I5 I6
Anti-image Covariance I1
.854 -.068
-.014 -.029
-.082 .073
I2 -.068
.899 -.002
-.048 .009
.000 I3
-.014 -.002
.239 -.093
.030 .005
I4 -.029
-.048 -.093
.256 -.168
-.029 I5
-.082 .009
.030 -.168
.456 -.171
I6 .073
.000 .005
-.029 -.171
.756 I7
-.051 .073
-.113 -.017
.006 -.010
I8 -.098
.122 .065
-.121 .097
.112 I9
-.011 -.066
-.059 .040
-.016 .054
I10 .115
-.015 -.045
-.040 -.061
.054 Anti-image Correlation
I1 .560
a
-.078 -.031
-.061 -.131
.091 I2
-.078 .471
a
-.004 -.100
.013 .000
I3 -.031
-.004 .859
a
-.375 .090
.012 I4
-.061 -.100
-.375 .816
a
-.493 -.066
I5 -.131
.013 .090
-.493 .753
a
-.292 I6
.091 .000
.012 -.066
-.292 .662
a
I7 -.099
.139 -.418
-.062 .016
-.022 I8
-.151 .183
.190 -.341
.205 .182
I9 -.023
-.132 -.228
.148 -.043
.118 I10
.255 -.033
-.190 -.161
-.185 .127
a. Measures of Sampling AdequacyMSA
279
Anti-image Matrices
I7 I8
I9 I10
Anti-image Covariance I1
-.051 -.098
-.011 .115
I2 .073
.122 -.066
-.015 I3
-.113 .065
-.059 -.045
I4 -.017
-.121 .040
-.040 I5
.006 .097
-.016 -.061
I6 -.010
.112 .054
.054 I7
.309 -.122
-.058 .005
I8 -.122
.494 .004
-.050 I9
-.058 .004
.280 -.135
I10 .005
-.050 -.135
.238 Anti-image Correlation
I1 -.099
-.151 -.023
.255 I2
.139 .183
-.132 -.033
I3 -.418
.190 -.228
-.190 I4
-.062 -.341
.148 -.161
I5 .016
.205 -.043
-.185 I6
-.022 .182
.118 .127
I7 .877
a
-.312 -.199
.019 I8
-.312 .784
a
.011 -.144
I9 -.199
.011 .850
a
-.525 I10
.019 -.144
-.525 .848
a
a. Measures of Sampling AdequacyMSA
280
Communalities
Initial Extraction
I1 1.000
.564 I2
1.000 .415
I3 1.000
.799 I4
1.000 .805
I5 1.000
.747 I6
1.000 .720
I7 1.000
.755 I8
1.000 .665
I9 1.000
.785 I10
1.000 .833
Extraction Method: Principal Component Analysis.
Total Variance Explained
Compo nent
Initial Eigenvalues Extraction Sums of Squared Loadings
Total of Variance
Cumulative Total
of Variance Cumulative
1 4.609
46.086 46.086
4.609 46.086
46.086 2
1.375 13.748
59.834 1.375
13.748 59.834
3 1.105
11.051 70.885
1.105 11.051
70.885 4
.992 9.918
80.803 5
.529 5.293
86.096 6
.505 5.047
91.144 7
.337 3.368
94.512 8
.244 2.440
96.952 9
.158 1.576
98.528 10
.147 1.472
100.000 Extraction Method: Principal Component Analysis.
281
Total Variance Explained
Compo nent
Rotation Sums of Squared Loadings Total
of Variance Cumulative
1 4.565
45.647 45.647
2 1.337
13.367 59.013
3 1.187
11.872 70.885
Extraction Method: Principal Component Analysis.
Component Matrix
a
Component 1
2 3
I1 .205
-.077 .719
I2 .079
.440 -.464
I3 .890
.036 -.075
I4 .855
.224 .153
I5 .604
.586 .196
I6 -.228
.764 .291
I7 .851
-.153 .090
I8 .656
-.413 .252
I9 .837
-.051 -.287
I10 .874
.024 -.261
282
Extraction Method: Principal Component Analysis.
a. 3 components extracted.
Rotated Component Matrix
a
Component 1
2 3
I1 .123
.212 .710
I2 .138
.228 -.586
I3 .893
.027 .014
I4 .837
.288 .147
I5 .590
.632 .018
I6 -.245
.811 -.054
I7 .833
-.084 .234
I8 .617
-.266 .462
I9 .862
-.137 -.152
I10 .898
-.056 -.153
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 4 iterations.
Component Transformation Matrix
Compo nent
1 2
3 1
.994 .026
.109 2
.018 .922
-.387 3
-.111 .387
.916 Extraction Method: Principal Component
Analysis. Rotation Method: Varimax with Kaiser
Normalization.
283
284 FACTOR VARIABLES I1 I2 I3 I4 I5 I6 I7 I8 I9 I10 I11 I12 I13
MISSING LISTWISE ANALYSIS I1 I2 I3 I4 I5 I6 I7 I8 I9 I10 I11 I12 I13 PRINT UNIVARIATE INITIAL CORRELATION SIG DET KMO INV REPR AIC
EXTRACTION ROTATION PLOT EIGEN ROTATION CRITERIA MINEIGEN1 ITERATE25 EXTRACTION PC CRITERIA ITERATE100 ROTATION
QUARTIMAX METHOD=CORRELATION.
Factor Analysis
Notes
Output Created 01-Oct-2008 08:14:50
Comments Input
Active Dataset DataSet0
Filter none
Weight none
Split File none
N of Rows in Working Data File
115 Missing Value Handling
Definition of Missing MISSING=EXCLUDE: User-defined
missing values are treated as missing. Cases Used
LISTWISE: Statistics are based on cases with no missing values for any
variable used.
285
Syntax FACTOR
VARIABLES I1 I2 I3 I4 I5 I6 I7 I8 I9 I10 I11 I12 I13
MISSING LISTWISE ANALYSIS I1 I2 I3 I4 I5 I6 I7 I8 I9 I10
I11 I12 I13 PRINT UNIVARIATE INITIAL
CORRELATION SIG DET KMO INV REPR AIC EXTRACTION ROTATION
PLOT EIGEN ROTATION CRITERIA MINEIGEN1
ITERATE25 EXTRACTION PC
CRITERIA ITERATE100 ROTATION QUARTIMAX
METHOD=CORRELATION. Resources
Processor Time 0:00:00.624
Elapsed Time 0:00:00.000
Maximum Memory Required 21700 21,191K bytes
[DataSet0]
Descriptive Statistics
Mean Std. Deviation
Analysis N I1
.0168053 1.89268043
115 I2
.0167978 2.49752858
115 I3
.01618452 1.929186437
115 I4
.0162 3.19925
115 I5
.0001 1.41117
115 I6
.0088 2.41884
115 I7
.0392 2.30751
115 I8
.0079 1.26978
115
286
I9 .0430
2.37255 115
I10 .0199
3.02726 115
I11 1.2174
1.16063 115
I12 -.0086
1.29500 115
I13 .0468
2.81137 115
Correlation Matrix
a,b
I1 I2
I3 I4
I5 I6
I7 Correlation
I1 1.000
.850 .873
.670 .559
.638 .573
I2 .850
1.000 .628
.935 .687
.678 .581
I3 .873
.628 1.000
.551 .381
.505 .405
I4 .670
.935 .551
1.000 .642
.609 .474
I5 .559
.687 .381
.642 1.000
.889 .525
I6 .638
.678 .505
.609 .889
1.000 .560
I7 .573
.581 .405
.474 .525
.560 1.000
I8 .139
.132 .188
.155 .023
.150 -.015
I9 .655
.684 .495
.592 .604
.666 .910
I10 .315
.578 .216
.659 .496
.469 .419
I11 .224
.204 .189
.167 .101
.023 .057
I12 .026
.232 -.113
.262 .519
.070 .098
I13 .635
.678 .503
.610 .588
.665 .716
a. Determinant = ,000 b. This matrix is not positive definite.
Correlation Matrix
a,b
I8 I9
I10 I11
I12 I13
Correlation I1
.139 .655
.315 .224
.026 .635
I2 .132
.684 .578
.204 .232
.678 I3
.188 .495
.216 .189
-.113 .503
I4 .155
.592 .659
.167 .262
.610
287
I5 .023
.604 .496
.101 .519
.588 I6
.150 .666
.469 .023
.070 .665
I7 -.015
.910 .419
.057 .098
.716 I8
1.000 .024
.182 -.038
-.232 .053
I9 .024
1.000 .477
-.006 .071
.941 I10
.182 .477
1.000 .121
.205 .461
I11 -.038
-.006 .121
1.000 .177
-.057 I12
-.232 .071
.205 .177
1.000 .039
I13 .053
.941 .461
-.057 .039
1.000 a. Determinant = ,000
b. This matrix is not positive definite.
Communalities
Initial Extraction
I1 1.000
.908 I2
1.000 .885
I3 1.000
.827 I4
1.000 .812
I5 1.000
.821 I6
1.000 .717
I7 1.000
.755 I8
1.000 .814
I9 1.000
.930 I10
1.000 .651
I11 1.000
.706 I12
1.000 .808
I13 1.000
.851 Extraction Method: Principal
Component Analysis.
288
Total Variance Explained
Compo nent
Initial Eigenvalues Extraction Sums of Squared Loadings
Total of Variance
Cumulative Total
of Variance Cumulative
1 6.589
50.684 50.684
6.589 50.684
50.684 2
1.536 11.813
62.498 1.536
11.813 62.498
3 1.287
9.897 72.394
1.287 9.897
72.394 4
1.074 8.260
80.654 1.074
8.260 80.654
5 .769
5.916 86.570
6 .610
4.696 91.266
7 .501
3.855 95.121
8 .283
2.175 97.296
9 .240
1.847 99.143
10 .111
.857 100.000
11 1.017E-12
7.819E-12 100.000
12 7.117E-13
5.475E-12 100.000
13 3.739E-13
2.877E-12 100.000
Extraction Method: Principal Component Analysis.
Total Variance Explained
Compo nent
Rotation Sums of Squared Loadings Total
of Variance Cumulative
1 6.509
50.072 50.072
2 1.493
11.488 61.560
3 1.300
10.000 71.560
4 1.182
9.094 80.654
Extraction Method: Principal Component Analysis.
