PEMBAHASAN HASIL OUTPUT STRUCTIRAL EQUATION MODELLING DENGAN AMOS 20

PENJELASAN HASIL MODEL AWAL SEM (STRUCTURAL EQUATION MODELLING) DENGAN IBM AMOS 21 Oleh: Saugi Rasyid 5 juni 2013 (S1 Teknik Industri Universitas Muhammadiyah Malang)

OBSERVED (DIUKUR LAGSUNG)

UNOBSERVED (TIDAK DIUKUR LANSUNG)

CONTOH TAMPILAN

CONTOH DATA EXCEL YANG SUDAH DI INPUT KE AMOS 20

CARA MENGHITUNG ANALYZE > CALCULATE ESTIMATE

ANALYZE > CALCULATE ESTIMATE

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Text Output

Notes for Group (Group number 1)

The model is recursive. Sample size = 100

Jumlah responden 100

Analysis Summary Date and Time

Date: Wednesday, June 05, 2013 Time: 5:16:39 AM Title

Model loyalty 3 variable: Wednesday, June 05, 2013 5:16 AM Variable Summary (Group number 1) Your model contains the following variables (Group number 1)

Observed, endogenous variables citra care jujur letak lengkap harga layanan brand word beli Unobserved, endogenous variables loyalty

Variable yg dapat di ukur

Unobserved, exogenous variables trust e1 e2 e3 satisfaction e7 e6 e5 e4 e8 e9 e10 error Variable counts (Group number 1)

Number of variables in your model: Number of observed variables: Number of unobserved variables: Number of exogenous variables: Number of endogenous variables:

24 10 14 13 11

Notes for Model (Default model) Computation of degrees of freedom (Default model)

Number of distinct sample moments: Number of distinct parameters to be estimated: Degrees of freedom (55 - 23):

Chi-square = 34.245 SEMAKIN KECIL SEMAKIN BAIK

55 23 32

Result (Default model)

Minimum was achieved Chi-square = 34.245 Degrees of freedom = 32 Probability level = .360

Karena p 0.36 diatas 0,05, maka model overall fit

Estimates (Group number 1 - Default model) Scalar Estimates (Group number 1 - Default model)

KARENA P 0.29 > KESALAHAN 0.05 (5 %) HO DITERIMA MAKA TIDAK ADA HUBUNGAN

Maximum Likelihood Estimates Regression Weights: (Group number 1 - Default model)

loyalty <--- trust loyalty <--- satisfaction citra <--- trust

Estimate .242 .294 1.095

S.E. .233 .253 .299

C.R. 1.038 1.159 3.667

P .299 .246 ***

Label

care jujur letak lengkap harga layanan brand word beli

<--<--<--<--<--<--<--<--<---

Estimate .980 1.000 1.000 .976 .872 .892 .740 .798 1.000

trust trust satisfaction satisfaction satisfaction satisfaction loyalty loyalty loyalty

S.E. .258

C.R. 3.802

P ***

.270 .252 .270 .134 .139

3.618 3.462 3.303 5.509 5.747

*** *** *** *** ***

Label

Standardized Regression Weights: (Group number 1 - Default model)

loyalty loyalty citra care jujur letak lengkap harga layanan brand word beli

<--<--<--<--<--<--<--<--<--<--<--<---

Estimate .189 .214 .564 .676 .604 .553 .615 .551 .505 .653 .711 .844

trust satisfaction trust trust trust satisfaction satisfaction satisfaction satisfaction loyalty loyalty loyalty

0.189 menujukan seberapa kuat hubungan, semakin besar semakin kuat minimal 50 % (0,5), nilai < 0.5 ingat bukan 0.05 maka hubungan sangat lemah Estimate (0.189) < 0.5

Covariances: (Group number 1 - Default model) trust <--> satisfaction

Estimate .224

S.E. .088

C.R. 2.555

P .011

Label

Correlations: (Group number 1 - Default model)

trust <--> satisfaction

Estimate .531

Variances: (Group number 1 - Default model)

trust satisfaction error e1 e2 e3 e7 e6

Estimate .452 .394 .653 1.164 .516 .786 .895 .618

S.E. .175 .166 .163 .215 .126 .157 .162 .125

C.R. 2.581 2.378 4.001 5.417 4.104 5.004 5.518 4.938

P .010 .017 *** *** *** *** *** ***

Label

0.011 (1.1 %) Karena nilai kesalah kecil < 0.05 maka diterima

Estimate .688 .916 .549 .465 .302

e5 e4 e8 e9 e10

S.E. .124 .156 .098 .095 .114

C.R. 5.536 5.864 5.598 4.902 2.660

P *** *** *** *** .008

Label

Squared Multiple Correlations: (Group number 1 - Default model)

Estimate .124 .712 .505 .426 .255 .304 .378 .306 .365 .457 .318

loyalty beli word brand layanan harga lengkap letak jujur care citra

Minimization History (Default model)

Negative eigenvalue s

Iteratio n 0

e

6

1 2 3 4 5 6 7

e e e e e e e

0 1 0 0 0 0 0

Conditio n#

Smallest eigenvalu e -.225

38.003 -.012 32.814 114.768 129.307 138.187 139.051

Diamete r

F

9999.00 0 1.615 1.088 .614 .498 .119 .026 .001

250.22 1 87.445 61.531 38.245 34.840 34.251 34.245 34.245

NTrie s 0 20 3 5 1 1 1 1

Ratio 9999.00 0 .727 .000 .826 .938 1.035 1.016 1.001

Model Fit Summary TUJUAN : UNTUK MENGUKUR MODEL MENJELASAKAN DATA

CMIN Model Default model Saturated model Independence model

NPAR 23 55 10

CMIN 34.245 .000 222.121

DF 32 0 45

P .360

CMIN/DF 1.070

.000

4.936

34, 24 Jika Default Model berada dianatra BKA (222,121) BKB (0.000) maka baik

TUJUAN RMR: SEMAKIN DEKATNYA ANGKA SAMPEL PADA ESTIMASINYA

RMR (Root Mean Residual) , GFI (Goodness of Fit Index) RMR Tingkat kesalahan

Model Default model Saturated model Independence model

GFI dan AGFI Semakin mendekati 1 semakin baik

RMR .067 .000 .253

GFI .942 1.000 .637

AGFI .900

PGFI .548

.557

.521

TUJUAN : Baseline Antar Indikator Observed Tidak Berkorelasi Baseline Comparisons

Model Default model Saturated model Independence model

NFI Delta1 .846 1.000 .000

RFI rho1 .783 .000

NFI (NORMAL FIT INDEX)

IFI Delta2 .988 1.000 .000

TLI rho2 .982 .000

CFI .987 1.000 .000

SEMAKIN MENDEKATI 1 SEMAKIN BAIK

Parsimony-Adjusted Measures Tujuan Parsimony : untuk mengukur kefektifan model Model Default model Saturated model Independence model

PRATIO .711 .000 1.000

PNFI .601 .000 .000

PCFI .702 .000 .000

NCP 2.245 .000 177.121

LO 90 .000 .000 134.353

NCP

Model Default model Saturated model Independence model

HI 90 20.580 .000 227.423

FMIN

Model Default model Saturated model Independence model

FMIN .346 .000 2.244

F0 .023 .000 1.789

LO 90 .000 .000 1.357

HI 90 .208 .000 2.297

RMSEA

Model Default model Independence model

RMSEA .027 .199

LO 90 .000 .174

HI 90 .081 .226

PCLOSE .701 .000

AIC

Model Default model Saturated model Independence model

AIC 80.245 110.000 242.121

BCC 85.995 123.750 244.621

BIC 140.164 253.284 268.173

CAIC 163.164 308.284 278.173

ECVI

Model Default model

ECVI .811

LO 90 .788

HI 90 .996

MECVI .869

Karena Lebih kecil dari Satur ed Model maka fi

Model Saturated model Independence model

ECVI 1.111 2.446

LO 90 1.111 2.014

HI 90 1.111 2.954

MECVI 1.250 2.471

HOELTER

0.05 (5 %) 0.01 (1%)

Tujuan : kecukupan

Model Default model Independence model

HOELTER .05 134 28

HOELTER .01 155 32 Jumlah Responden 200

UJI NORMALITAS MULTIVARIAT SEM

Assessment of normality (Group number 1)

-2,58 > c.r skew, c.r skew, < 2.58 = NORMAL Variable beli word brand layanan harga lengkap letak jujur care citra Multivariate

min 7.000 7.000 7.000 7.000 7.000 7.000 7.000 5.000 7.000 1.000

max 10.000 10.000 10.000 10.000 10.000 10.000 10.000 10.000 10.000 10.000

skew -.628 -.941 -.762 -.768 -.855 -.808 -.597 -.828 -.628 -2.363

c.r. -2.562 -3.840 -3.109 -3.133 -3.490 -3.298 -2.438 -3.380 -2.564 -9.648

kurtosis -.758 -.140 -.474 -.811 -.548 -.562 -1.136 .092 -.644 11.027 27.710

ALAT UKUR PENTING

DATA OUT LIER

c.r. -1.548 -.286 -.968 -1.656 -1.119 -1.147 -2.318 .188 -1.314 22.509 8.943

SEMAKIN BESAR OUT LIER

DATA YANG DIHAPUS

Observations farthest from the centroid (Mahalanobis distance) (Group number 1)

Observation number 57 24 15 14 28 25 89 23 27

Mahalanobis d-squared 44.690 29.083 25.468 24.647 22.418 21.868 20.565 18.763 18.363

p1 .000 .001 .005 .006 .013 .016 .024 .043 .049

p2 .000 .007 .011 .003 .010 .005 .011 .069 .058

NORMAL KARENA BRADA DIANTARA -2,58 > c.r skew, c.r skew, < 2.58 = NORMAL

Observation number 66 30 18 19 26 31 92 32 91 52 13 82 81 88 54 79 4 51 2 38 29 87 80 6 93 68 22 56 83 63 58 50 39 78 48 34 8 21 20 33 94 3 47 86 77 36

Mahalanobis d-squared 18.200 17.560 16.919 16.306 16.218 15.993 15.887 14.297 14.245 14.120 13.839 13.734 13.657 13.412 13.402 13.321 13.261 13.000 12.874 12.761 12.559 12.518 12.365 12.092 11.746 11.433 11.332 10.724 10.718 10.672 10.585 10.545 10.522 10.208 10.034 10.006 9.739 9.707 9.435 9.346 9.271 9.223 8.900 8.694 8.660 8.299

p1 .052 .063 .076 .091 .094 .100 .103 .160 .162 .168 .180 .185 .189 .202 .202 .206 .209 .224 .231 .237 .249 .252 .261 .279 .302 .325 .332 .379 .380 .384 .391 .394 .396 .422 .437 .440 .464 .467 .491 .500 .507 .511 .542 .561 .565 .600

p2 .034 .050 .078 .123 .083 .072 .050 .432 .353 .312 .344 .301 .251 .274 .203 .169 .132 .160 .148 .132 .146 .112 .112 .152 .237 .330 .311 .614 .537 .486 .463 .409 .346 .477 .518 .458 .568 .512 .628 .615 .592 .548 .704 .769 .726 .867

Observation number 37 11 90 10 9 70 69 49 55 41 16 67 85 17 74 71 44 72 35 5 46 53 98 99 65 61 64 12 7 1 96 75 95 42 73 59 97 84 40 76 60 100 62 45 43

Mahalanobis d-squared 8.203 8.198 7.918 7.887 7.792 7.662 7.582 6.977 6.840 6.817 6.757 6.487 6.264 5.790 5.403 5.386 4.855 4.526 4.362 4.330 4.289 4.268 4.224 4.212 4.104 3.851 3.851 3.844 3.775 3.722 3.696 3.550 3.462 3.334 3.131 3.034 3.034 2.936 2.833 2.709 2.680 2.680 2.218 2.201 .121

p1 .609 .609 .637 .640 .649 .662 .670 .728 .740 .743 .748 .773 .793 .833 .863 .864 .901 .921 .930 .931 .933 .934 .937 .937 .943 .954 .954 .954 .957 .959 .960 .965 .968 .972 .978 .981 .981 .983 .985 .987 .988 .988 .994 .995 1.000

p2 .866 .819 .900 .873 .871 .884 .876 .988 .990 .985 .982 .993 .997 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 .999 .998 .993 .967 .981 .896 1.000