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BAB V KESIMPULAN

5.2 Saran

5.2.2 Bagi Peneliti Selanjutnya

Saran yang dapat diberikan kepada peneliti selanjutnya yang ingin meneliti tema tentang restoran di Indonesia adalah sebagai berikut:

1. Melakukan pengujian kembali dengan menggunakan penelitian yang serupa, namun ada baiknya jika mengganti objek yang berbeda dari penelitian yang telah dilakukan. Hal tersebut bertujuan untuk melihat apakah hasil pada objek yang berbeda memiliki perbedaan yang lebih baik.

2. Menambahkan variabel atau faktor-faktor lain yang dapat mempengaruhi kepuasan konsumen. Jika penelitian selanjutnya menggunakan kuesioner online, ada baiknya setiap indikator dari masing-masing variabel diperhatikan agar responden dapat

memahami maksud dari pertanyaan yang diberikan dan hasil yang diperoleh nantinya dapat sesuai dengan keinginan yang akan dicapai.

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LAMPIRAN

Lampiran 1: Kuesioner Penelitian

Lampiran 1: Kuesioner Penelitian (Lanjutan)

Lampiran 1: Kuesioner Penelitian (Lanjutan)

Lampiran 1: Kuesioner Penelitian (Lanjutan)

Lampiran 1: Kuesioner Penelitian (Lanjutan)

Lampiran 1: Kuesioner Penelitian (Lanjutan)

Lampiran 1: Kuesioner Penelitian (Lanjutan)

Lampiran 1: Kuesioner Penelitian (Lanjutan)

Lampiran 2: Hasil Uji Validitas Pre-test 1. Service Quality

KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .741 Bartlett's Test of Sphericity Approx. Chi-Square 74.668

df 6

Sig. .000

Anti-image Matrices

SQ1 SQ2 SQ3 SQ4

Anti-image Covariance SQ1 .679 -.151 -.242 -.166

SQ2 -.151 .832 -.089 -.127

SQ3 -.242 -.089 .707 -.167

SQ4 -.166 -.127 -.167 .756

Anti-image Correlation SQ1 .711a -.201 -.349 -.232

SQ2 -.201 .796a -.115 -.160

SQ3 -.349 -.115 .722a -.229

SQ4 -.232 -.160 -.229 .765a

a. Measures of Sampling Adequacy (MSA)

Component Matrixa

Component

1

SQ1 .787

SQ2 .642

SQ3 .760

SQ4 .728

Extraction Method:

Principal Component Analysis.

a. 1 components extracted.

Lampiran 2: Hasil Uji Validitas Pre-test (Lanjutan) 2. Price Fairness

KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .813 Bartlett's Test of Sphericity Approx. Chi-Square 160.503

df 6

Sig. .000

Anti-image Matrices

PF1 PF2 PF3 PF4

Anti-image Covariance PF1 .538 -.145 -.183 -.095

PF2 -.145 .545 -.156 -.129

PF3 -.183 -.156 .487 -.146

PF4 -.095 -.129 -.146 .623

Anti-image Correlation PF1 .809a -.267 -.358 -.165

PF2 -.267 .819a -.303 -.221

PF3 -.358 -.303 .784a -.266

PF4 -.165 -.221 -.266 .849a

a. Measures of Sampling Adequacy (MSA)

Component Matrixa

Component

1

PF1 .823

PF2 .823

PF3 .852

PF4 .777

Extraction Method:

Principal Component Analysis.

a. 1 components extracted.

Lampiran 2: Hasil Uji Validitas Pre-test (Lanjutan) 3. Food Quality

KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .832 Bartlett's Test of Sphericity Approx. Chi-Square 277.255

df 15

Sig. .000

Anti-image Matrices

FQ1 FQ2 FQ3 FQ4

Anti-image Covariance FQ1 .579 -.098 -.125 .003

FQ2 -.098 .514 -.227 -.101

FQ3 -.125 -.227 .534 .033

FQ4 .003 -.101 .033 .502

FQ5 -.167 -.006 -.011 -.083

FQ6 -.023 -.028 -.081 -.208

Anti-image Correlation FQ1 .868a -.180 -.224 .006

FQ2 -.180 .832a -.433 -.198

FQ3 -.224 -.433 .816a .064

FQ4 .006 -.198 .064 .818a

FQ5 -.309 -.011 -.021 -.166

FQ6 -.047 -.061 -.172 -.458

a. Measures of Sampling Adequacy (MSA)

Component Matrixa Component

1

FQ1 .739

FQ2 .766

FQ3 .737

FQ4 .752

FQ5 .779

FQ6 .825

Extraction Method:

Principal Component Analysis.

a. 1 components extracted.

Lampiran 2: Hasil Uji Validitas Pre-test (Lanjutan) 4. Customer Satisfaction

KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .862 Bartlett's Test of Sphericity Approx. Chi-Square 250.083

df 10

Sig. .000

Anti-image Matrices

CS1 CS2 CS3 CS4

Anti-image Covariance CS1 .578 .006 -.094 -.116

CS2 .006 .457 -.154 -.131

CS3 -.094 -.154 .454 -.121

CS4 -.116 -.131 -.121 .446

CS5 -.158 -.121 -.059 -.077

Anti-image Correlation CS1 .871a .012 -.184 -.228

CS2 .012 .843a -.337 -.291

CS3 -.184 -.337 .860a -.269

CS4 -.228 -.291 -.269 .863a

CS5 -.288 -.249 -.123 -.159

a. Measures of Sampling Adequacy (MSA)

Component Matrixa

Component

1

CS1 .759

CS2 .826

CS3 .837

CS4 .845

CS5 .806

Extraction Method:

Principal Component Analysis.

a. 1 components extracted.

Lampiran 2: Hasil Uji Validitas Pre-test (Lanjutan) 5. Price Fairness

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .688 Bartlett's Test of Sphericity Approx. Chi-Square 91.573

df 3

Sig. .000

Anti-image Matrices

RI1 RI2 RI3

Anti-image Covariance RI1 .543 -.262 -.237

RI2 -.262 .618 -.131

RI3 -.237 -.131 .654

Anti-image Correlation RI1 .649a -.453 -.398

RI2 -.453 .700a -.206

RI3 -.398 -.206 .729a

a. Measures of Sampling Adequacy (MSA)

Component Matrixa

Component

1

RI1 .869

RI2 .825

RI3 .807

Extraction Method:

Principal Component Analysis.

a. 1 components extracted.

Lampiran 3: Hasil Uji Reliabilitas Pre-test 1. Service Quality

Reliability Statistics Cronbach's

Alpha N of Items

.698 4

2. Price Fairness

Reliability Statistics Cronbach's

Alpha N of Items

.834 4

3. Food Quality

Reliability Statistics Cronbach's

Alpha N of Items

.858 6

4. Customer Satisfaction

Reliability Statistics Cronbach's

Alpha N of Items

.873 5

5. Revisit Intention

Reliability Statistics Cronbach's

Alpha N of Items

.781 3

Lampiran 4: Path Diagram Measurement Model

Lampiran 5: Output Standardized Regression Weight

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

Estimate SQ4 <--- SQ ,622 SQ3 <--- SQ ,725 SQ2 <--- SQ ,820 SQ1 <--- SQ ,643 FQ6 <--- FQ ,772 FQ5 <--- FQ ,790 FQ4 <--- FQ ,811 FQ3 <--- FQ ,790 FQ2 <--- FQ ,693 FQ1 <--- FQ ,681 PF4 <--- PF ,790 PF3 <--- PF ,745 PF2 <--- PF ,790 PF1 <--- PF ,652 CS5 <--- CS ,825 CS4 <--- CS ,813 CS3 <--- CS ,651 CS2 <--- CS ,883 CS1 <--- CS ,688 RI3 <--- RI ,721 RI2 <--- RI ,800 RI1 <--- RI ,886

Lampiran 6: Structural Model

Lampiran 7: Regression Weight

Regression Weights: (Group number 1 - Default model)

Estimate S.E. C.R. P Label

CS <--- SQ ,264 ,080 3,304 ***

CS <--- FQ ,533 ,118 4,515 ***

CS <--- PF ,434 ,098 4,412 ***

RI <--- CS 1,082 ,182 5,935 ***

SQ1 <--- SQ 1,000

SQ2 <--- SQ 1,229 ,206 5,964 ***

SQ3 <--- SQ 1,133 ,195 5,817 ***

SQ4 <--- SQ ,876 ,171 5,110 ***

PF1 <--- PF 1,000

PF2 <--- PF 1,186 ,179 6,618 ***

PF3 <--- PF 1,401 ,208 6,733 ***

PF4 <--- PF 1,324 ,197 6,738 ***

FQ1 <--- FQ 1,000

FQ2 <--- FQ 1,161 ,209 5,558 ***

FQ3 <--- FQ 1,367 ,205 6,657 ***

FQ4 <--- FQ 1,254 ,182 6,871 ***

FQ5 <--- FQ 1,240 ,188 6,609 ***

FQ6 <--- FQ 1,287 ,200 6,439 ***

RI1 <--- RI 1,000

RI2 <--- RI ,977 ,123 7,949 ***

RI3 <--- RI ,950 ,141 6,754 ***

CS4 <--- CS 1,101 ,193 5,711 ***

CS5 <--- CS 1,063 ,185 5,761 ***

CS3 <--- CS ,902 ,197 4,585 ***

CS2 <--- CS 1,102 ,181 6,083 ***

CS1 <--- CS 1,000

Lampiran 8: Model Fit Summary

Computation of degrees of freedom (Default model) Number of distinct sample moments: 253 Number of distinct parameters to be estimated: 48 Degrees of freedom (253 - 48): 205

Result (Default model) Minimum was achieved Chi-square = 644,120 Degrees of freedom = 205 Probability level = ,000

CMIN

Model NPAR CMIN DF P CMIN/DF

Default model 48 644,120 205 ,000 3,142

Saturated model 253 ,000 0

Independence model 22 1987,241 231 ,000 8,603

Baseline Comparisons

Model NFI RFI IFI TLI

Delta1 rho1 Delta2 rho2 CFI

Default model ,676 ,635 ,754 ,718 ,750

Saturated model 1,000 1,000 1,000

Independence model ,000 ,000 ,000 ,000 ,000

RMSEA

Model RMSEA LO 90 HI 90 PCLOSE

Default model ,140 ,128 ,152 ,000

Independence model ,264 ,253 ,275 ,000

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