PEOU2 -.211 -.863 -.589 -1.202 Estimate S.E. C.R. P Label ...U NIDIMENSIONALITAS CSE Estimasi Skalar...

UN

IDIM

ENSIO

NA

LITAS

PEO

UPengujian NormalitasEstimasi Skalar

Diagram Jalur Awal Konstruk

Diagram Jalur Akhir & Nilai GOF

Estimate S.E. C.R. P Label

Bobot Regresi

PEOU2 <--- PEOU 1.000

PEOU3 <--- PEOU 1.000

PEOU1 <--- PEOU .956 .100 9.519 *** par_1

Bobot Regresi (Standard)

PEOU2 <--- PEOU .834



Varian

PEOU .252 .045 5.645 *** par_2

ePEOU2 .110 .024 4.579 *** par_3

ePEOU3 .117 .025 4.745 *** par_4

ePEOU1 .124 .026 4.760 *** par_5

Squared Multiple Correlations (R2)

PEOU1 .649

PEOU3 .682

PEOU2 .696

Variable skew c.r. kurtosis c.r.

PEOU1 -.067 -.275 -.341 -.696

PEOU3 -.044 -.180 -.283 -.578

PEOU2 -.211 -.863 -.589 -1.202

Multivariate 1.344 1.227

Number of distinct sample moments: 6

Number of distinct parameters to be estimated: 5

Degrees of freedom (6 - 5): 1

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Muhamad R. Setyadji - 9108205801

UN

IDIM

ENSIO

NA

LITAS

CSE

Pengujian NormalitasEstimasi Skalar




Bobot Regresi

CSE1 <--- CSE 1.000

CSE2 <--- CSE 1.081 .166 6.509 *** par_1

CSE4 <--- CSE 1.000


CSE1 <--- CSE .765

CSE2 <--- CSE .726

CSE4 <--- CSE .719

Varian

CSE .236 .049 4.804 *** par_2

eCSE1 .167 .037 4.512 *** par_3

eCSE2 .247 .053 4.617 *** par_4

eCSE4 .220 .042 5.210 *** par_5


CSE4 .517

CSE2 .528

CSE1 .585


CSE4 -.065 -.266 -.716 -1.461

CSE2 -.137 -.559 -1.079 -2.203

CSE1 -.108 -.442 -.639 -1.304





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UN

IDIM

ENSIO

NA

LITAS

SAN

XPengujian NormalitasEstimasi Skalar




Bobot Regresi

SANX3 <--- SANX 1.000

SANX4 <--- SANX 1.000

SANX2 <--- SANX 1.000


SANX3 <--- SANX .914



Kovarian

eSANX3 <--> zSANX .071 .031 2.275 .023 par_1

Korelasi

eSANX3 <--> zSANX .526

Varian

zSANX .486 .082 5.924 *** par_2

eSANX4 .096 .026 3.657 *** par_3

eSANX3 .037 .024 1.547 .122 par_4

eSANX2 .412 .063 6.573 *** par_5


SANX .000

SANX2 .542

SANX3 .944

SANX4 .836


SANX2 .339 1.384 -.668 -1.363

SANX3 .329 1.343 -.435 -.887

SANX4 .327 1.337 -.259 -.529





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UN

IDIM

ENSIO

NA

LITAS

OU





Bobot Regresi

OU1 <--- OU 1.000

OU2 <--- OU 1.201 .116 10.383 *** par_1

OU3 <--- OU 1.000


OU1 <--- OU .736

OU2 <--- OU .974

OU3 <--- OU .794

Varian

OU .255 .051 5.047 *** par_2

eOU1 .216 .036 5.953 *** par_3

eOU2 .020 .028 .700 .484 par_4

eOU3 .150 .029 5.203 *** par_5


OU3 .630

OU2 .949

OU1 .541


OU3 -.340 -1.390 -.065 -.132

OU2 .065 .267 -.271 -.552

OU1 -.479 -1.955 .474 .968





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UN

IDIM

ENSIO

NA

LITAS

OQ





Bobot Regresi

1.000

OQ2 <--- OQ 1.031 .110 9.403 *** par_1

OQ3 <--- OQ 1.000


OQ1 <--- OQ 0.838

OQ2 <--- OQ 0.867

OQ3 <--- OQ 0.731

Varian

OQ 0.288 0.054 5.28 *** par_2

eOQ1 0.122 0.03 4.11 *** par_3

eOQ2 0.102 0.031 3.29 0 par_4

eOQ3 0.251 0.043 5.83 *** par_5


OQ3 0.534

OQ2 0.751

OQ1 0.703


OQ3 -.157 -.642 -.274 -.560

OQ2 -.274 -1.118 .241 .491

OQ1 -.340 -1.387 .324 .662





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UN

IDIM

ENSIO

NA

LITAS

SNPengujian NormalitasEstimasi Skalar




Bobot Regresi

SN1 <--- SN 1.000

SN2 <--- SN 1.000

SN3 <--- SN 1.000

SN3 <--- SN1 -.283 .076 -3.735 *** par_1


SN1 <--- SN .937

SN2 <--- SN .938

SN3 <--- SN .969

SN3 <--- SN1 -.292

Varian

SN .453 .069 6.568 *** par_2

eSN1 .063 .018 3.429 *** par_3

eSN2 .062 .018 3.477 *** par_4

eSN3 .244 .039 6.251 *** par_5


SN1 .878

SN3 .494

SN2 .879

skew c.r. kurtosis c.r.

SN1 -.028 -.115 -.037 -.075

SN3 -.062 -.254 -.355 -.724

SN2 .000 .000 .090 .185





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UN

IDIM

ENSIO

NA

LITAS

IMG





Bobot Regresi

IMG2 <--- IMG 1.000

IMG3 <--- IMG 1.000

IMG1 <--- IMG 1.102 .100 11.039 *** par_1


IMG2 <--- IMG .822

IMG3 <--- IMG .837

IMG1 <--- IMG .874

Varian

IMG .426 .076 5.640 *** par_2

eIMG2 .205 .040 5.096 *** par_3

eIMG3 .182 .038 4.796 *** par_4

eIMG1 .160 .043 3.738 *** par_5


IMG1 .764

IMG3 .701

IMG2 .675


IMG1 -.033 -.135 -.761 -1.553

IMG3 -.072 -.294 .336 .687

IMG2 .062 .253 -.373 -.762





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UN

IDIM

ENSIO

NA

LITAS

REL





Bobot Regresi

REL2 <--- REL 1.000

REL3 <--- REL 1.000

REL1 <--- REL 1.000


REL2 <--- REL .854

REL3 <--- REL 1.017

REL1 <--- REL .864

Kovarian

eREL3 <--> zREL .071 .031 2.275 .023 par_1

Korelasi

eREL3 <--> zREL .526

Varian

zREL .345 .058 5.909 *** par_2

eREL2 .128 .029 4.416 *** par_3

eREL3 .161 .033 4.909 *** par_4

eREL1 .117 .028 4.185 *** par_5


REL .000

REL1 .746

REL3 .519

REL2 .730


REL1 .012 .048 -.314 -.641

REL3 -.037 -.152 -.293 -.598

REL2 .130 .532 -.173 -.354

Multivariate .744 .679




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UN

IDIM

ENSIO

NA

LITAS

BI





Bobot Regresi

BI2 <--- BI .733 .113 6.506 *** par_1

BI3 <--- BI 1.000

BI1 <--- BI 1.000


BI2 <--- BI .596

BI3 <--- BI .846

BI1 <--- BI .902

Varian

BI .300 .050 6.056 *** par_2

eBI2 .292 .045 6.482 *** par_3

eBI3 .119 .027 4.385 *** par_4

eBI1 .069 .023 2.945 .003 par_5


BI1 .814

BI3 .716

BI2 .356


BI1 -.295 -1.206 -.647 -1.321

BI3 .191 .778 -.079 -.162

BI2 .100 .409 -.314 -.640





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UN

IDIM

ENSIO

NA

LITAS

VO

LPengujian NormalitasEstimasi Skalar




Bobot Regresi

VOL3 <--- VOL 1.583 .705 2.246 .025 par_1

VOL4 <--- VOL 1.000

VOL2 <--- VOL 1.000


VOL3 <--- VOL .756

VOL4 <--- VOL .449

VOL2 <--- VOL .451

Varian

VOL .103 .052 1.979 .048 par_2

eVOL3 .194 .123 1.576 .115 par_3

eVOL4 .406 .073 5.558 *** par_4

eVOL2 .402 .073 5.535 *** par_5


VOL2 .204

VOL4 .202

VOL3 .571


VOL2 -.397 -1.621 -.141 -.289

VOL4 -.362 -1.479 .165 .338

VOL3 -.292 -1.193 .357 .728





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UN

IDIM

ENSIO

NA

LITAS

USE





Bobot Regresi

SANX1 <--- USE 1

OU4 <--- USE 1

USE1 <--- USE 0.635 0.25 2.58 0.01 par_1


SANX1 <--- USE 0.496

OU4 <--- USE 0.664

USE1 <--- USE 0.408

Varian

USE 0.178 0.057 3.14 0 par_2

eSANX1 0.543 0.091 5.95 *** par_3

eOU4 0.225 0.058 3.85 *** par_4

eUSE1 0.358 0.061 5.85 *** par_5


USE1 0.166

OU4 0.441

SANX1 0.246


USE1 .436 1.780 .650 1.328

OU4 -.298 -1.218 -.485 -.991

SANX1 -.264 -1.076 -.811 -1.655

Multivariate -.195 -.178




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MO

DEL

STR

UK

TUR

AL

Path Diagram Tahap-1

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25 Agustus 2010


ESTIM

ASIB

AYESIA

NT

AH

AP-1

Estimasi Loading Factor

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25 Agustus 2010


OU CSE VOL SN OQ SANX REL IMG PEOU PU BI USE

SN1 0.000 0.000 0.000 0.914 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

VOL4 0.000 0.000 0.590 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

VOL2 0.000 0.000 0.636 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

VOL3 0.000 0.000 0.739 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

SN2 0.000 0.000 0.000 0.923 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

SN3 0.000 0.000 0.000 0.945 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

Mean S.E. S.D. C.S.

50%

Lower

bound

50%

Upper

bound

Min Max

SN 0.701 0.004 0.079 1.001 0.648 0.750 0.448 1.163

VOL 0.289 0.002 0.050 1.001 0.254 0.322 0.105 0.512

eSN1 0.126 0.001 0.022 1.001 0.111 0.139 0.057 0.222

eSN3 0.307 0.002 0.034 1.001 0.282 0.329 0.186 0.454

eSN2 0.126 0.001 0.022 1.001 0.111 0.139 0.056 0.229

eVOL3 0.293 0.004 0.065 1.002 0.252 0.335 0.007 0.565

eVOL2 0.434 0.003 0.057 1.001 0.395 0.469 0.260 0.742

eVOL4 0.537 0.003 0.062 1.001 0.493 0.577 0.334 0.811

Estimasi Varian

Variabel Moderasi

MO

DEL

STR

UK

TUR

AL

Path Diagram Tahap-2

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25 Agustus 2010


UJIV

ALID

ITAS

DA

NK

ECO

CO

KA

N

Uji Average Variance Extracted

Konstruk AVE Valid? Konstruk AVE Valid?

PU 0.710688 √ SN 0.818048 √

PEOU 0.553777 √ IMG 0.683815 √

CSE 0.475622 - REL 0.729999 √

SANX 0.60078 √ BI 0.484272 -

OU 0.559035 √ VOL 0.439673 -

OQ 0.571561 √ USE 0.27311 -

Uji Reliabilitas Konstruk

Konstruk CR Reliabel? Konstruk CR Reliabel?

PU 0.907425 √ SN 0.930959 √

PEOU 0.787302 √ IMG 0.866101 √

CSE 0.730124 √ REL 0.88923 √

SANX 0.816826 √ BI 0.737145 √

OU 0.791505 √ VOL 0.7018 √

OQ 0.799231 √ USE 0.498063 √

Uji Validitas Diskriminan Fit Measures

25 Agustus 2010

49Muhamad R. Setyadji - 9108205801

PU PEOU CSE SANX OU OQ SN IMG REL BI VOL USE

PU 0.843

PEOU 0.550 0.744

CSE 0.648 0.910 0.690

SANX -0.230 -0.174 -0.191 0.775

OU 0.589 0.740 0.829 -0.192 0.748

OQ 0.394 0.615 0.682 -0.111 0.697 0.756

SN 0.389 0.525 0.618 0.068 0.616 0.595 0.904

IMG 0.354 0.542 0.530 0.015 0.574 0.520 0.672 0.827

REL 0.548 0.671 0.742 -0.083 0.753 0.654 0.621 0.638 0.854

BI 0.527 0.564 0.593 -0.181 0.611 0.592 0.448 0.496 0.692 0.696

VOL 0.467 0.647 0.785 -0.026 0.781 0.633 0.300 0.407 0.610 0.895 0.663

USE 0.854 0.780 0.935 -0.197 0.975 0.554 0.661 0.571 0.710 0.736 0.748 0.523

UJIH

IPO

TESAB

IIN

TPoligon Frekuensi

25 Agustus 2010


Trace Plot

Mean S.D.95% Lower

bound95% Upper

bound Skewness Kurtosis Min Max

BI<--Int 0.002 0.001 0 0.004 0.082 0.123 -0.002 0.006

UJIH

IPO

TESAP

U

SNPoligon Frekuensi

25 Agustus 2010


Trace Plot

Mean S.D.95% Lower

bound95% Upper

bound Skewness Kurtosis Min Max

PU<--SN 0.129 0.075 -0.016 0.283 0.116 0.045 -0.154 0.435

PEOU2 -.211 -.863 -.589 -1.202 Estimate S.E. C.R. P Label ...U NIDIMENSIONALITAS CSE Estimasi Skalar...

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Transcript of PEOU2 -.211 -.863 -.589 -1.202 Estimate S.E. C.R. P Label ...U NIDIMENSIONALITAS CSE Estimasi Skalar...