Lampiran Output SPSS UJI NORMALITAS

  Lampiran Output SPSS UJI NORMALITAS

  

One-Sample Kolmogorov-Smirnov Test

  Unstandardiz Unstandardized ed Residual Residual N

  31

  31

  a,,b

  Normal Parameters Mean .0000000 .0000000 Std. Deviation 17.97442009 1.54183458

  Most Extreme Absolute .177 .095 Differences

  Positive .177 .068 Negative -.116 -.095

  Kolmogorov-Smirnov Z .985 .530 Asymp. Sig. (2-tailed)

  .286 .942

  c c

  Monte Carlo Sig. (2- Sig. .258 .968 tailed) 95% Confidence Lower Bound .104 .906 Interval

  Upper Bound .412 1.000 a. Test distribution is Normal.

  b. Calculated from data.

  c. Based on 31 sampled tables with starting seed 926214481.

  Uji Multi Kolinearitas

  Variables Entered/Removed

  Variables Variables Model Entered Removed Method

  a

  1 X8, X7, X6 . Enter a. All requested variables entered.

  b Model Summary

  Adjusted R Std. Error of Model R R Square Square the Estimate

  a

  1 .653 .426 .362 18.947

  a. Predictors: (Constant), X8, X7, X6

  b. Dependent Variable: Y1

  b ANOVA

  Sum of df Model Squares Mean Square F Sig.

  a

  3

  1 Regression 7186.962 2395.654 6.674 .002

  27 Residual 9692.393 358.978

  30 Total 16879.355

  a. Predictors: (Constant), X8, X7, X6

  b ANOVA

  Sum of df Model Squares Mean Square F Sig.

  a

  3

  1 Regression 7186.962 2395.654 6.674 .002

  27 Residual 9692.393 358.978

  30 Total 16879.355

  a. Predictors: (Constant), X8, X7, X6

  b. Dependent Variable: Y1

  a

Coefficients

  Standardize Unstandardized d Collinearity

  Coefficients Coefficients Statistics Std. Model B Error Beta t Sig. Tolerance VIF 1 (Constant) 13.907 5.073 2.741 .011

  X6 46.222 38.502 .176 1.200 .240 .989 1.011 X7 .815 2.484 .048 .328 .745 .999 1.001 X8 27.311 6.600 .607 4.138 .000 .989 1.012

  a. Dependent Variable: Y1

  b Model Summary

  Adjusted R Std. Error of Model R R Square Square the Estimate

  a

  1 .463 .214 .057 1.68900

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

  b. Dependent Variable: Y2

  b ANOVA

  Sum of Model Squares df Mean Square F Sig.

  a

  1 Regression 19.421 5 3.884 1.362 .272 Residual 71.318 25 2.853 Total 90.739

  30

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

  b. Dependent Variable: Y2

  

Coefficients

a

  Model Unstandardized

  Coefficients Standardized

  Coefficients t Sig.

  Collinearity Statistics

  B Std. Error Beta Toleranc e

  VIF 1 (Constant) 32.409 .561 57.754 .000 X1 1.136 .830 .276 1.370 .183 .772 1.296 X2 3.139 8.201 .081 .383 .705 .705 1.419 X3 .742 .552 .289 1.344 .191 .680 1.471 X4 -.181 1.175 -.035 -.154 .879 .619 1.614 X5 -.336 .669 -.098 -.503 .620 .825 1.212

  a. Dependent Variable: Y2

  Uji Heterokedasitas Coefficients a

  Model Unstandardized

  Coefficients Standardized

  Coefficients t Sig. B Std. Error Beta 1 (Constant) 10.807 2.720 3.974 .000

  X6 17.083 20.643 .143 .828 .415 X7 -1.560 1.332 -.202 -1.172 .251 X8 7.412 3.539 .363 2.095 .046

  a. Dependent Variable: ABRES_Y1

  Charts

  

Coefficients

a

  Model Unstandardized

  Coefficients Standardized

  Coefficients t Sig. B Std. Error Beta 1 (Constant) 1.443 .269 5.368 .000

  X1 .134 .398 .066 .337 .739 X2 4.847 3.929 .253 1.234 .229 X3 -.660 .265 -.521 -2.494 .020 X4 -.329 .563 -.128 -.584 .565 X5 .178 .321 .105 .555 .584

  a. Dependent Variable: ABRES_Y2

  Charts

  Hasil Hipotesis Hipotesis Pertama b Variables Entered/Removed

  Variables Variables Model Entered Removed Method

  a

  1 X1 . Enter a. All requested variables entered.

  b. Dependent Variable: Y2

  Model Summary

  Adjusted R Std. Error of Model R R Square Square the Estimate

  a

  1 .359 .129 .099 1.65064

  a. Predictors: (Constant), X1

  b ANOVA

  Sum of Model Squares df Mean Square F Sig.

  a

  1 Regression 11.725 1 11.725 4.303 .047 Residual 79.014 29 2.725 Total 90.739

  30

  a. Predictors: (Constant), X1

  b. Dependent Variable: Y2

  a

Coefficients

  Unstandardized Standardized Coefficients Coefficients Model B Std. Error Beta t Sig.

  1 (Constant) 32.653 .374 87.368 .000 X1 1.478 .712 .359 2.074 .047

  a. Dependent Variable: Y2

  Hipotesis Kedua b Variables Entered/Removed

  Variables Variables Model Entered Removed Method

  a

  1 X2 . Enter a. All requested variables entered.

  b. Dependent Variable: Y2

  Model Summary

  Adjusted R Std. Error of Model R R Square Square the Estimate

  a

  1 .101 .010 -.024 1.75975

  Model Summary

  Adjusted R Std. Error of Model R R Square Square the Estimate

  a

  1 .101 .010 -.024 1.75975

  a. Predictors: (Constant), X2

  b ANOVA

  Sum of Model Squares df Mean Square F Sig.

  a

  1 Regression .934 1 .934 .302 .587 Residual 89.805 29 3.097 Total 90.739

  30

  a. Predictors: (Constant), X2

  b. Dependent Variable: Y2

  a

Coefficients

  Unstandardized Standardized Coefficients Coefficients Model B Std. Error Beta t Sig.

  1 (Constant) 32.959 .437 75.439 .000 X2 3.939 7.173 .101 .549 .587

  a. Dependent Variable: Y2

  Hipotesis Ketiga b Variables Entered/Removed

  Variables Variables Model Entered Removed Method

  a

  1 X3 . Enter a. All requested variables entered.

  b. Dependent Variable: Y2

  Model Summary

  Adjusted R Std. Error of Model R R Square Square the Estimate

  a

  1 .380 .145 .115 1.63603

  Model Summary

  Adjusted R Std. Error of Model R R Square Square the Estimate

  a

  1 .380 .145 .115 1.63603

  a. Predictors: (Constant), X3

  b ANOVA

  Sum of Model Squares df Mean Square F Sig.

  a

  1 Regression 13.118 1 13.118 4.901 .035 Residual 77.621 29 2.677 Total 90.739

  30

  a. Predictors: (Constant), X3

  b. Dependent Variable: Y2

  a Coefficients

  Unstandardized Standardized Coefficients Coefficients Model B Std. Error Beta t Sig.

  1 (Constant) 32.512 .404 80.550 .000 X3 .976 .441 .380 2.214 .035

  a

Coefficients

  Unstandardized Standardized Coefficients Coefficients Model B Std. Error Beta t Sig.

  1 (Constant) 32.512 .404 80.550 .000 X3 .976 .441 .380 2.214 .035

  a. Dependent Variable: Y2

  Hipotesis Keempat b Variables Entered/Removed

  Variables Variables Model Entered Removed Method

  a

  1 X4 . Enter a. All requested variables entered.

  b. Dependent Variable: Y2

  Model Summary

  Adjusted R Std. Error of Model R R Square Square the Estimate

  a

  1 .152 .023 -.011 1.74843

  a. Predictors: (Constant), X4

  b ANOVA

  Sum of Model Squares df Mean Square F Sig.

  a

  1 Regression 2.086 1 2.086 .682 .416 Residual 88.653 29 3.057 Total 90.739

  30

  a. Predictors: (Constant), X4

  b. Dependent Variable: Y2

  a Coefficients

  Unstandardized Standardized Coefficients Coefficients Model B Std. Error Beta t Sig.

  1 (Constant) 32.854 .454 72.319 .000 X4 .791 .958 .152 .826 .416

  a. Dependent Variable: Y2

  Hipotesis Kelima b Variables Entered/Removed

  Variables Variables Model Entered Removed Method

  a

  1 X5 . Enter a. All requested variables entered.

  b. Dependent Variable: Y2

  Model Summary

  Adjusted R Std. Error of Model R R Square Square the Estimate

  a

  1 .018 .000 -.034 1.76858

  a. Predictors: (Constant), X5

  b ANOVA

  Sum of Model Squares df Mean Square F Sig.

  a

  1 Regression .030 1 .030 .010 .922 Residual 90.709 29 3.128 Total 90.739

  30

  a. Predictors: (Constant), X5

  b. Dependent Variable: Y2

  a

Coefficients

  Unstandardized Standardized Coefficients Coefficients Model B Std. Error Beta t Sig.

  1 (Constant) 33.159 .470 70.523 .000 X5 -.063 .636 -.018 -.098 .922

  a. Dependent Variable: Y2

  Hipotesis Keenam b Variables Entered/Removed

  Variables Variables Model Entered Removed Method

  a

  1 X6 . Enter a. All requested variables entered.

  b. Dependent Variable: Y1

  Model Summary

  Adjusted R Std. Error of Model R R Square Square the Estimate

  a

  1 .240 .058 .025 23.420

  a. Predictors: (Constant), X6

  b ANOVA

  Sum of Model Squares df Mean Square F Sig.

  a

  1 Regression 973.577 1 973.577 1.775 .193 Residual 15905.778 29 548.475 Total 16879.355

  30

  a. Predictors: (Constant), X6

  b. Dependent Variable: Y1

  a Coefficients

  Unstandardized Standardized Coefficients Coefficients Model B Std. Error Beta t Sig.

  1 (Constant) 25.977 4.924 5.276 .000 X6 63.055 47.328 .240 1.332 .193

  a

Coefficients

  Unstandardized Standardized Coefficients Coefficients Model B Std. Error Beta t Sig.

  1 (Constant) 25.977 4.924 5.276 .000 X6 63.055 47.328 .240 1.332 .193

  a. Dependent Variable: Y1

  Hipotesis Ketujuh b Variables Entered/Removed

  Variables Variables Model Entered Removed Method

  a

  1 X7 . Enter a. All requested variables entered.

  b. Dependent Variable: Y1

  Model Summary

  Adjusted R Std. Error of Model R R Square Square the Estimate

  a

  1 .066 .004 -.030 24.072

  a. Predictors: (Constant), X7

  b ANOVA

  Sum of odel Squares df Mean Square F Sig.

  a

  1 Regression 74.397 1 74.397 .128 .723 Residual 16804.958 29 579.481 Total 16879.355

  30

  a. Predictors: (Constant), X7

  b. Dependent Variable: Y1

  a Coefficients

  Unstandardized Standardized Coefficients Coefficients Model B Std. Error Beta t Sig.

  1 (Constant) 28.691 4.740 6.054 .000 X7 1.130 3.154 .066 .358 .723

  a. Dependent Variable: Y1

  Hipotesis Kedelapan b Variables Entered/Removed

  Variables Variables Model Entered Removed Method

  a

  1 X8 . Enter a. All requested variables entered.

  b. Dependent Variable: Y1

  Model Summary

  Adjusted R Std. Error of Model R R Square Square the Estimate

  a

  1 .627 .393 .372 18.802

  a. Predictors: (Constant), X8

  b ANOVA

  Sum of Model Squares df Mean Square F Sig.

  a

  1 Regression 6627.209 1 6627.209 18.746 .000 Residual 10252.146 29 353.522 Total 16879.355

  30

  a. Predictors: (Constant), X8

  b. Dependent Variable: Y1

  a Coefficients

  Unstandardized Standardized Coefficients Coefficients Model B Std. Error Beta t Sig.

  1 (Constant) 16.505 4.501 3.667 .001 X8 28.194 6.512 .627 4.330 .000

  a. Dependent Variable: Y1

  Analisis Jalur PersamaanStrukturPertama Variables Entered/Removed

  Variables Variables Model Entered Removed Method

  a

  1 X8, X7, X6 . Enter a. All requested variables entered.

  Model Summary

  Adjusted R Std. Error of Model R R Square Square the Estimate

  a

  1 .653 .426 .362 18.947

  a. Predictors: (Constant), X8, X7, X6

  b ANOVA

  Sum of Model Squares df Mean Square F Sig.

  a

  1 Regression 7186.962 3 2395.654 6.674 .002

  Residual 9692.393 27 358.978 Total 16879.355

  a. Dependent Variable: Y1

  a

  X8

  1 Y1, X7, X6,

  Entered Variables Removed Method

  Model Variables

  PERSAMAAN STRUKTUR KEDUA Variables Entered/Removed

  1 (Constant) 13.907 5.073 2.741 .011 X6 46.222 38.502 .176 1.200 .240 X7 .815 2.484 .048 .328 .745 X8 27.311 6.600 .607 4.138 .000

  30

  Coefficients B Std. Error Beta t Sig.

  Coefficients Standardized

  Model Unstandardized

  

Coefficients

a

  b. Dependent Variable: Y1

  a. Predictors: (Constant), X8, X7, X6

  . Enter a. All requested variables entered.

  Model Summary

  Adjusted R Std. Error of Model R R Square Square the Estimate

  a

  1 .556 .309 .203 1.55269

  a. Predictors: (Constant), Y1, X7, X6, X8

  b ANOVA

  Sum of Model Squares df Mean Square F Sig.

  a

  1 Regression 28.057 4 7.014 2.909 .041 Residual 62.682 26 2.411 Total 90.739

  30

  a. Predictors: (Constant), Y1, X7, X6, X8

  b. Dependent Variable: Y2

  Coefficients a

  Model Unstandardized

  Coefficients Standardized

  Coefficients B Std. Error Beta t Sig.

  1 (Constant) 31.881 .470 67.827 .000 X6 1.790 3.238 .093 .553 .585 X7 .076 .204 .061 .375 .711 X8 -.225 .691 -.068 -.325 .748 Y1 .041 .016 .558 2.595 .015

  a. Dependent Variable: Y2