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Transcript of etheses.uin-malang.ac.idetheses.uin-malang.ac.id/662/11/10510012...

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9 4 3 4 3 3 3 4 2 3 3 3 3 3 3 3 3 3 2 3 3 3 3 1 9 9 9 9 8 1

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9 .0

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100

2.0

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101

3.0

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102

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103

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104

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105

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106

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11.0

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107

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108

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0 1

1

1

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Lampiran 2 : Distribusi Item

Frequencies

statistics

uni

k

var

iati

f

ino

vat

if

ny

am

an

am

an

se

na

ng

mu

rah

mah

al

terj

an

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au

pe

ma

sar

an

pe

nju

ala

n

ikl

an

pusat

perbel

anjaan

dekat

deng

an

konsu

men

dilalui

bany

ak

orang

ny

am

an

me

ny

en

an

gk

an

ra

ma

h

Key

akin

an

Me

mbe

li

Rek

ome

nda

si

Ke

bia

sa

an

Pem

beli

an

ulan

g

N Valid 11

1

11

1

11

1

11

1

11

1

11

1

11

1 111

11

1 111

11

1

11

1 111 111 111

11

1

11

1

11

1 111 111

11

1 111

Missi

ng 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Mean 2.6

8

3.1

6

3.0

6

2.8

9

3.0

4

2.9

0

2.7

3 2.43

3.0

5

2.7

9

2.5

0

2.5

0 3.04 3.15 3.33

2.7

3

2.8

6

2.5

0 2.82 2.57

2.6

6 2.79

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Lampiran 3 : validitas dan reliabilitas

Correlations

X1

unik Pearson Correlation .783**

Sig. (2-tailed) .000

N 111

variatif Pearson Correlation .760**

Sig. (2-tailed) .000

N 111

inovatif Pearson Correlation .785**

Sig. (2-tailed) .000

N 111

**. Correlation is significant at the 0.01 level (2-

tailed).

Reliability Statistics

Cronbach's

Alpha N of Items

.673 3

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Correlations

X2

nyaman Pearson Correlation .862**

Sig. (2-tailed) .000

N 111

aman Pearson Correlation .860**

Sig. (2-tailed) .000

N 111

senang Pearson Correlation .845**

Sig. (2-tailed) .000

N 111

**. Correlation is significant at the 0.01 level (2-

tailed).

Reliability Statistics

Cronbach's

Alpha N of Items

.817 3

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Correlations

X3

murah Pearson Correlation .828**

Sig. (2-tailed) .000

N 111

mahal Pearson Correlation .658**

Sig. (2-tailed) .000

N 111

terjangkau Pearson Correlation .868**

Sig. (2-tailed) .000

N 111

**. Correlation is significant at the 0.01 level (2-

tailed).

Reliability Statistics

Cronbach's

Alpha N of Items

.696 3

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Correlations

X4

pemasaran Pearson Correlation .863**

Sig. (2-tailed) .000

N 111

penjualan Pearson Correlation .814**

Sig. (2-tailed) .000

N 111

iklan Pearson Correlation .882**

Sig. (2-tailed) .000

N 111

**. Correlation is significant at the 0.01 level (2-

tailed).

Reliability Statistics

Cronbach's

Alpha N of Items

.814 3

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Correlations

X5

pusat perbelanjaan Pearson Correlation .878**

Sig. (2-tailed) .000

N 111

dekat dengan konsumen Pearson Correlation .914**

Sig. (2-tailed) .000

N 111

dilalui banyak orang Pearson Correlation .818**

Sig. (2-tailed) .000

N 111

**. Correlation is significant at the 0.01 level (2-tailed).

Reliability Statistics

Cronbach's

Alpha N of Items

.840 3

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Correlations

X6

nyaman Pearson Correlation .856**

Sig. (2-tailed) .000

N 111

menyenangkan Pearson Correlation .857**

Sig. (2-tailed) .000

N 111

ramah Pearson Correlation .824**

Sig. (2-tailed) .000

N 111

**. Correlation is significant at the 0.01 level (2-tailed).

Reliability Statistics

Cronbach's

Alpha N of Items

.798 3

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Correlations

Y

Keyakinan Membeli Pearson Correlation .867**

Sig. (2-tailed) .000

N 111

Rekomendasi Pearson Correlation .749**

Sig. (2-tailed) .000

N 111

Kebiasaan Pearson Correlation .778**

Sig. (2-tailed) .000

N 111

Pembelian ulang Pearson Correlation .822**

Sig. (2-tailed) .000

N 111

**. Correlation is significant at the 0.01 level (2-tailed).

Reliability Statistics

Cronbach's

Alpha N of Items

.818 4

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Lampiran 4 : Multikolinieritas

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .600a .361 .324 1.10081

a. Predictors: (Constant), X6, X5, X1, X3, X4, X2

ANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression 71.055 6 11.842 9.773 .000a

Residual 126.026 104 1.212

Total 197.081 110

a. Predictors: (Constant), X6, X5, X1, X3, X4, X2

b. Dependent Variable: Y

Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig.

Collinearity Statistics

B Std. Error Beta Tolerance VIF

1 (Constant) 1.672 1.356 1.233 .220

X1 .272 .108 .230 2.529 .013 .742 1.348

X2 -.032 .105 -.033 -.304 .762 .526 1.900

X3 .206 .115 .153 1.794 .076 .848 1.179

X4 .232 .081 .274 2.865 .005 .670 1.492

X5 .215 .093 .196 2.316 .023 .860 1.163

X6 .183 .111 .158 1.651 .102 .672 1.488

a. Dependent Variable: Y

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Lampiran 5 : Normalitas

NPar Tests

One-Sample Kolmogorov-Smirnov Test

Unstandardized

Residual

N 111

Normal Parametersa Mean .0000000

Std. Deviation 1.07037082

Most Extreme Differences Absolute .111

Positive .062

Negative -.111

Kolmogorov-Smirnov Z 1.173

Asymp. Sig. (2-tailed) .128

a. Test distribution is Normal.

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Lampiran 6 : Linieritas

Model Summary and Parameter Estimates

Dependent Variable:Y

Equation

Model Summary Parameter Estimates

R Square F df1 df2 Sig. Constant b1

Linear .178 23.623 1 109 .000 6.394 .499

The independent variable is X1.

Model Summary and Parameter Estimates

Dependent Variable:Y

Equation

Model Summary Parameter Estimates

R Square F df1 df2 Sig. Constant b1

Linear .130 16.268 1 109 .000 7.739 .351

The independent variable is X2.

Model Summary and Parameter Estimates

Dependent Variable:Y

Equation

Model Summary Parameter Estimates

R Square F df1 df2 Sig. Constant b1

Linear .090 10.759 1 109 .001 7.524 .403

The independent variable is X3.

Model Summary and Parameter Estimates

Dependent Variable:Y

Equation

Model Summary Parameter Estimates

R Square F df1 df2 Sig. Constant b1

Linear .208 28.606 1 109 .000 7.832 .386

The independent variable is X4.

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Model Summary and Parameter Estimates

Dependent Variable:Y

Equation

Model Summary Parameter Estimates

R Square F df1 df2 Sig. Constant b1

Linear .088 10.571 1 109 .002 7.731 .326

The independent variable is X5.

Model Summary and Parameter Estimates

Dependent Variable:Y

Equation

Model Summary Parameter Estimates

R Square F df1 df2 Sig. Constant b1

Linear .085 10.117 1 109 .002 8.109 .337

The independent variable is X6.

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Lampiran 7 : Regresi

Regression

Descriptive Statistics

Mean Std. Deviation N

Y 10.8378 1.33852 111

X1 8.9099 1.13257 111

X2 8.8288 1.37427 111

X3 8.2162 .99458 111

X4 7.7838 1.58059 111

X5 9.5225 1.21989 111

X6 8.0901 1.15640 111

Correlations

Y X1 X2 X3 X4 X5 X6

Pearson Correlation Y 1.000 .422 .360 .300 .456 .297 .291

X1 .422 1.000 .393 .171 .456 .133 .173

X2 .360 .393 1.000 .273 .485 .211 .548

X3 .300 .171 .273 1.000 .117 .318 .141

X4 .456 .456 .485 .117 1.000 .111 .334

X5 .297 .133 .211 .318 .111 1.000 -.008

X6 .291 .173 .548 .141 .334 -.008 1.000

Sig. (1-tailed) Y . .000 .000 .001 .000 .001 .001

X1 .000 . .000 .037 .000 .082 .035

X2 .000 .000 . .002 .000 .013 .000

X3 .001 .037 .002 . .111 .000 .070

X4 .000 .000 .000 .111 . .123 .000

X5 .001 .082 .013 .000 .123 . .467

X6 .001 .035 .000 .070 .000 .467 .

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N Y 111 111 111 111 111 111 111

X1 111 111 111 111 111 111 111

X2 111 111 111 111 111 111 111

X3 111 111 111 111 111 111 111

X4 111 111 111 111 111 111 111

X5 111 111 111 111 111 111 111

X6 111 111 111 111 111 111 111

Variables Entered/Removedb

Model

Variables

Entered

Variables

Removed Method

1 X6, X5, X1, X3,

X4, X2a

. Enter

a. All requested variables entered.

b. Dependent Variable: Y

Model Summaryb

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate Durbin-Watson

1 .600a .361 .324 1.10081 2.468

a. Predictors: (Constant), X6, X5, X1, X3, X4, X2

b. Dependent Variable: Y

ANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression 71.055 6 11.842 9.773 .000a

Residual 126.026 104 1.212

Total 197.081 110

a. Predictors: (Constant), X6, X5, X1, X3, X4, X2

b. Dependent Variable: Y

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Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig.

Correlations

B Std. Error Beta Zero-order Partial Part

1 (Constant) 1.672 1.356 1.233 .220

X1 .272 .108 .230 2.529 .013 .422 .241 .198

X2 -.032 .105 -.033 -.304 .762 .360 -.030 -.024

X3 .206 .115 .153 1.794 .076 .300 .173 .141

X4 .232 .081 .274 2.865 .005 .456 .271 .225

X5 .215 .093 .196 2.316 .023 .297 .221 .182

X6 .183 .111 .158 1.651 .102 .291 .160 .129

a. Dependent Variable: Y

Residuals Statisticsa

Minimum Maximum Mean Std. Deviation N

Predicted Value 8.7341 12.7923 10.8378 .80371 111

Residual -3.11471 3.31569 .00000 1.07037 111

Std. Predicted Value -2.618 2.432 .000 1.000 111

Std. Residual -2.829 3.012 .000 .972 111

a. Dependent Variable: Y