4. Tabel Total Keragaman
Component Initial Eigenvalues
Extraction Sums of Squared Loadings Total
of Variance
Cumulative Total
of Variance
Cumulative 1
3.567 59.445
59.445 3.567
59.445 59.445
2 1.140
19.000 78.446
1.140 19.000
78.446 3
.487 8.121
86.567 4
.368 6.131
92.697 5
.296 4.927
97.625 6
.143 2.375
100.000
Extraction Method: Principal Component Analysis
5. Tabel Matrik Komponen
Component 1
2 Tujuan
.901 .064
Perlengkapan .756
-.443 Feedback
.899 .070
Perasaan .320
.864 Rekan
.821 .255
Hasil .773
-.352
Extraction Method: Principal Component Analysis. a 2 components extracted
6. Tabel Matrik Komponen dirotasi
Component 1
2 Tujuan
.814 .392
Perlengkapan .866
-.133 Feedback
.809 .397
Perasaan -.021
.921 Rekan
.669 .540
Hasil .849
-.041
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.
a Rotation converged in 3 iterations.
7. Tabel Matrik Transformasi Komponen
Component 1
2 1
.929 .369
2 -.369
.929
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.
Lampiran 7. Hasil Perhitungan Analisis Faktor untuk Komponen Proses dengan Bantuan Software SPSS 15.0 for Windows
1. KMO and Bartletts Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.
.796 Bartletts Test
of Sphericity Approx. Chi-Square
879.501 Df
91 Sig.
.000
2. Tabel Anti-image Matrices
Anti-image Matrices
B1 B2
B3 B4
B5 B6
B7 B8
B9 B10
B11 B12
B13 B14
Anti-image Covariance B1
.626 -.024
.057 -.028
.051 -.134
-.096 .031
-.032 .036
.006 .003
.031 -.132
B2 -.024
.100 -.076
-.052 .029
-.018 -.061
.034 -.049
-.043 -.047
.006 .045
.008 B3
.057 -.076
.182 -.028
-.049 .014
.011 -.024
.022 .039
.058 .009
-.058 -.055
B4 -.028
-.052 -.028
.172 -.054
.074 .031
-.041 .039
3.21E- 005
.007 -.080
-.049 .066
B5 .051
.029 -.049
-.054 .245
-.106 -.064
-.006 -.089
.011 -.030
-.023 .080
.002 B6
-.134 -.018
.014 .074
-.106 .282
.072 -.123
.046 -.042
-.007 -.039
-.068 -.061
B7 -.096
-.061 .011
.031 -.064
.072 .343
-.110 .105
-.092 -.001
.087 -.038
-.143 B8
.031 .034
-.024 -.041
-.006 -.123
-.110 .351
-.096 .109
-.047 .034
.018 -.019
B9 -.032
-.049 .022
.039 -.089
.046 .105
-.096 .157
-.072 .052
-.061 -.047
-.003 B10
.036 -.043
.039 3.21E-
005 .011
-.042 -.092
.109 -.072
.249 .007
-.018 -.042
.069 B11
.006 -.047
.058 .007
-.030 -.007
-.001 -.047
.052 .007
.213 -.033
-.123 .031
B12 .003
.006 .009
-.080 -.023
-.039 .087
.034 -.061
-.018 -.033
.304 .027
-.114 B13
.031 .045
-.058 -.049
.080 -.068
-.038 .018
-.047 -.042
-.123 .027
.153 -.008
B14 -.132
.008 -.055
.066 .002
-.061 -.143
-.019 -.003
.069 .031
-.114 -.008
.491 Anti-image Correlation
B1 .750a
-.097 .168
-.084 .130
-.318 -.207
.066 -.103
.091 .016
.007 .101
-.238 B2
-.097 .806a
-.561 -.401
.185 -.105
-.328 .180
-.388 -.270
-.321 .034
.364 .035
B3 .168
-.561 .847a
-.161 -.234
.062 .045
-.094 .132
.181 .293
.039 -.350
-.184 B4
-.084 -.401
-.161 .846a
-.261 .335
.126 -.167
.235 .000
.037 -.351
-.305 .226
B5 .130
.185 -.234
-.261 .813a
-.402 -.221
-.020 -.455
.042 -.131
-.083 .415
.007 B6
-.318 -.105
.062 .335
-.402 .782a
.232 -.391
.218 -.156
-.030 -.134
-.329 -.163
B7 -.207
-.328 .045
.126 -.221
.232 .634a
-.317 .451
-.315 -.004
.271 -.165
-.349 B8
.066 .180
-.094 -.167
-.020 -.391
-.317 .794a
-.409 .367
-.173 .104
.080 -.046
B9 -.103
-.388 .132
.235 -.455
.218 .451
-.409 .756a
-.364 .287
-.279 -.303
-.012 B10
.091 -.270
.181 .000
.042 -.156
-.315 .367
-.364 .849a
.029 -.067
-.215 .198
B11 .016
-.321 .293
.037 -.131
-.030 -.004
-.173 .287
.029 .796a
-.128 -.682
.096 B12
.007 .034
.039 -.351
-.083 -.134
.271 .104
-.279 -.067
-.128 .878a
.125 -.296
B13 .101
.364 -.350
-.305 .415
-.329 -.165
.080 -.303
-.215 -.682
.125 .733a
-.031 B14
-.238 .035
-.184 .226
.007 -.163
-.349 -.046
-.012 .198
.096 -.296
-.031 .720a
a Measures of Sampling AdequacyMSA
3. Tabel Komunalitas
Kategori