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LAMPIRAN Hasil Korelasi Pearson

  • Kebisingan dengan Jenis Kereta
  • Model Summary

  1 Regression 12,182 1 12,182 ,363 ,549

  1 (Constant) 84,588 1,872 45,187 ,000 jenis kereta

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

  Coefficients a

  b. Predictors: (Constant), jenis kereta

  a. Dependent Variable: kebisingan kereta api

  86

  Residual 2853,657 85 33,572 Total 2865,839

  b

  ANOVA a Model Sum of Squares df Mean Square F Sig.

  b. Dependent Variable: kebisingan kereta api

  a. Predictors: (Constant), jenis kereta

  ,004 -,007 5,7942 ,921

  a

  Durbin-Watson 1 ,065

  Std. Error of the Estimate

  Model R R Square Adjusted R Square

  

b

  

LAMPIRAN

Hasil Korelasi Pearson

  • ,771 1,280 -,065 -,602 ,549

  a. Dependent Variable: kebisingan kereta api

  • Kebisingan dengan Jenis kereta dan panjang rangk
  • Model Summary

  a. Dependent Variable: kebisingan kereta api

  a. Predictors: (Constant), kecepatan kereta api, jenis kereta

  ,004 -,019 5,8279 ,924

  a

  Durbin-Watson 1 ,067

  Std. Error of the Estimate

  Model R R Square Adjusted R Square

  

b

  ,210 ,260 ,130 ,808 ,421 jenis kereta -1,899 1,895 -,161 -1,002 ,319 a. Dependent Variable: kebisingan kereta api

  1 (Constant) 84,304 1,908 44,174 ,000 panjang rangkaian

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

  Coefficients a

  b. Predictors: (Constant), jenis kereta, panjang rangkaian

  86

  Residual 2831,624 84 33,710 Total 2865,839

  b

  1 Regression 34,216 2 17,108 ,508 ,604

  ANOVA a Model Sum of Squares df Mean Square F Sig.

  b. Dependent Variable: kebisingan kereta api

  a. Predictors: (Constant), jenis kereta, panjang rangkaian

  ,012 -,012 5,8060 ,924

  a

  Durbin-Watson 1 ,109

  Std. Error of the Estimate

  Model R R Square Adjusted R Square

  

b

  • Kebisingan dengan Jenis kereta dan Kecepatan kereta
  • Model Summary

  b. Dependent Variable: kebisingan kereta api

  a ANOVA Model Sum of Squares df Mean Square F Sig. b

  Regression 12,790 2 6,395 ,188 ,829

  1 Residual 2853,050 84 33,965 Total 2865,839

  86

  a. Dependent Variable: kebisingan kereta api

  b. Predictors: (Constant), kecepatan kereta api, jenis kereta

  a Coefficients Model Unstandardized Standardized t Sig.

  Coefficients Coefficients B Std. Error Beta

  (Constant) 85,859 9,689 8,861 ,000 jenis kereta -,856 1,436 -,072 -,596 ,553 1 kecepatan

  • ,025 ,185 -,016 -,134 ,894 kereta api

  a. Dependent Variable: kebisingan kereta api

  • Kebisingan dengan Jenis kereta dan jarak pengukuran

  

b

Model Summary -

  Model R R Square Adjusted R Std. Error of the Durbin-Watson Square Estimate

  a

  1 ,736 ,542 ,531 3,9540 2,004

  a. Predictors: (Constant), jarak alat, jenis kereta

  b. Dependent Variable: kebisingan kereta api

  a ANOVA Model Sum of Squares df Mean Square F Sig. b

  Regression 1552,548 2 776,274 49,652 ,000

  1 Residual 1313,291 84 15,634 Total 2865,839

  86

  a. Dependent Variable: kebisingan kereta api

  b. Predictors: (Constant), jarak alat, jenis kereta

  • ,771 ,874 -,065 -,883 ,380 jarak alat -1,031 ,104 -,733 -9,926 ,000
    • >Kebisingan dengan Jenis kereta, panjang rangkaian dan kecepatan ke
  • Model Summary

  ,012 -,024 5,8408 ,925

  a. Dependent Variable: kebisingan kereta api

  86

  Residual 2831,543 83 34,115 Total 2865,839

  b

  1 Regression 34,296 3 11,432 ,335 ,800

  ANOVA a Model Sum of Squares df Mean Square F Sig.

  b. Dependent Variable: kebisingan kereta api

  a. Predictors: (Constant), kecepatan kereta api, panjang rangkaian, jenis kereta

  a

  Coefficients a

  Durbin-Watson 1 ,109

  Std. Error of the Estimate

  Model R R Square Adjusted R Square

  

b

  a. Dependent Variable: kebisingan kereta api

  1 (Constant) 110,355 2,893 38,142 ,000 jenis kereta

  Standardized Coefficients t Sig. B Std. Error Beta

  Model Unstandardized Coefficients

  b. Predictors: (Constant), kecepatan kereta api, panjang rangkaian, jenis kereta

  a Coefficients Model Unstandardized Standardized T Sig.

  Coefficients Coefficients B Std. Error Beta

  (Constant) 84,772 9,807 8,644 ,000 jenis kereta -1,923 1,969 -,163 -,977 ,332 panjang

  1 ,209 ,263 ,129 ,794 ,429 rangkaian kecepatan

  • ,009 ,186 -,006 -,049 ,961 kereta api

  a. Dependent Variable: kebisingan kereta api

  • Kebisingan dengan Jenis kereta, panjang rangkaian dan jarak pengukuran

  

b

Model Summary -

  Model R R Square Adjusted R Std. Error of the Durbin-Watson Square Estimate

  a

  1 ,741 ,549 ,533 3,9443 2,031

  a. Predictors: (Constant), jarak alat, panjang rangkaian, jenis kereta

  b. Dependent Variable: kebisingan kereta api

  a ANOVA b

  Regression 1574,581 3 524,860 33,737 ,000

  1 Residual 1291,258 83 15,557 Total 2865,839

  86

  a. Dependent Variable: kebisingan kereta api

  b. Predictors: (Constant), jarak alat, panjang rangkaian, jenis kereta

  a Coefficients Model Unstandardized Standardized t Sig.

  Coefficients Coefficients B Std. Error Beta

  (Constant) 110,071 2,896 38,008 ,000 jenis

  • 1,899 1,287 -,161 -1,475 ,144 kereta

  1 panjang ,210 ,176 ,130 1,190 ,237 rangkaian jarak alat -1,031 ,104 -,733 -9,950 ,000

  a. Dependent Variable: kebisingan kereta api

  • Kebisingan dengan Jenis kereta, kecepatan kereta dan jarak pengukuran

  

b

Model Summary -

  Model R R Square Adjusted R Std. Error of the Durbin-Watson Square Estimate

  a

  1 ,736 ,542 ,525 3,9769 2,012

  a. Predictors: (Constant), kecepatan kereta api, jarak alat, jenis kereta

  b. Dependent Variable: kebisingan kereta api

  a ANOVA b

  Regression 1553,155 3 517,718 32,735 ,000

  1 Residual 1312,684 83 15,815 Total 2865,839

  86

  a. Dependent Variable: kebisingan kereta api

  b. Predictors: (Constant), kecepatan kereta api, jarak alat, jenis kereta

  a Coefficients Model Unstandardized Standardized T Sig.

  Coefficients Coefficients B Std. Error Beta

  (Constant) 111,626 7,109 15,703 ,000 jenis kereta -,856 ,980 -,072 -,874 ,385 1 jarak alat -1,031 ,104 -,733 -9,869 ,000 kecepatan

  • ,025 ,126 -,016 -,196 ,845 kereta api

  a. Dependent Variable: kebisingan kereta api

  • Kebisingan dengan Panjang rangkaian

  

b

Model Summary -

  Model R R Square Adjusted R Std. Error of the Durbin-Watson Square Estimate

  a

  1 ,011 ,000 -,012 5,8062 ,934

  a. Predictors: (Constant), panjang rangkaian

  b. Dependent Variable: kebisingan kereta api

  a ANOVA Model Sum of Squares Df Mean Square F Sig. b

  Regression ,371 1 ,371 ,011 ,917

  1 Residual 2865,468 85 33,711 Total 2865,839

  86

  a. Dependent Variable: kebisingan kereta api

  b. Predictors: (Constant), panjang rangkaian

  • Kebisingan dengan Panjang rangkaian dan kecepatan ke
  • Model Summary

  ,001 -,023 5,8392 ,929

  a. Dependent Variable: kebisingan kereta api

  86

  Total 2865,839

  b

  Regression 1,762 2 ,881 ,026 ,975

  ANOVA a Model Sum of Squares df Mean Square F Sig.

  b. Dependent Variable: kebisingan kereta api

  a. Predictors: (Constant), kecepatan kereta api, panjang rangkaian

  a

  Coefficients a

  Durbin-Watson 1 ,025

  Std. Error of the Estimate

  Model R R Square Adjusted R Square

  

b

  a. Dependent Variable: kebisingan kereta api

  ,018 ,176 ,011 ,105 ,917

  1 (Constant) 83,363 1,661 50,176 ,000 panjang rangkaian

  Standardized Coefficients t Sig. B Std. Error Beta

  Model Unstandardized Coefficients

  b. Predictors: (Constant), kecepatan kereta api, panjang rangkaian

  a Coefficients Model Unstandardized Standardized t Sig.

  Coefficients Coefficients B Std. Error Beta

  (Constant) 81,530 9,225 8,838 ,000 panjang ,034 ,192 ,021 ,175 ,862 1 rangkaian kecepatan

  ,036 ,180 ,024 ,202 ,840 kereta api a. Dependent Variable: kebisingan kereta api

  • Kebisingan dengan Panjang rangkaian dan jarak pengukuran

  

b

Model Summary -

  Model R R Square Adjusted R Std. Error of the Durbin-Watson Square Estimate

  a

  1 ,733 ,538 ,527 3,9718 2,021

  a. Predictors: (Constant), jarak alat, panjang rangkaian

  b. Dependent Variable: kebisingan kereta api

  a ANOVA Model Sum of Squares df Mean Square F Sig. b

  1 Residual 1325,103 84 15,775 Total 2865,839

  86

  a. Dependent Variable: kebisingan kereta api

  b. Predictors: (Constant), jarak alat, panjang rangkaian

  • Kebisingan dengan Kecepatan ke
  • Model Summary

  ,000 -,012 5,8058 ,929

  a. Dependent Variable: kebisingan kereta api

  86

  Residual 2865,120 85 33,707 Total 2865,839

  b

  1 Regression ,719 1 ,719 ,021 ,884

  ANOVA a Model Sum of Squares Df Mean Square F Sig.

  b. Dependent Variable: kebisingan kereta api

  a. Predictors: (Constant), kecepatan kereta api

  a

  Coefficients a

  Durbin-Watson 1 ,016

  Std. Error of the Estimate

  Model R R Square Adjusted R Square

  

b

  ,018 ,120 ,011 ,153 ,878 jarak alat -1,031 ,104 -,733 -9,882 ,000 a. Dependent Variable: kebisingan kereta api

  1 (Constant) 109,130 2,845 38,365 ,000 panjang rangkaian

  Standardized Coefficients t Sig. B Std. Error Beta

  Model Unstandardized Coefficients

  b. Predictors: (Constant), kecepatan kereta api

  a Coefficients Model Unstandardized Standardized t Sig.

  Coefficients Coefficients B Std. Error Beta

  (Constant) 82,399 7,729 10,661 ,000

  1 kecepatan ,024 ,165 ,016 ,146 ,884 kereta api a. Dependent Variable: kebisingan kereta api

  • Kebisingan dengan Kecepatan kereta dan jarak pengukuran

  

b

  • Model Summary Model R R Square Adjusted R Std. Error of the Durbin-Watson

  Square Estimate

  a

  1 ,733 ,538 ,527 3,9713 2,010

  a. Predictors: (Constant), kecepatan kereta api, jarak alat

  b. Dependent Variable: kebisingan kereta api

  a ANOVA Model Sum of Squares Df Mean Square F Sig. b

  Regression 1541,085 2 770,542 48,859 ,000

  1 Residual 1324,754 84 15,771 Total 2865,839

  86

  a. Dependent Variable: kebisingan kereta api

  b. Predictors: (Constant), kecepatan kereta api, jarak alat

  a Coefficients Model Unstandardized Coefficients Standardized t Sig.

  Coefficients B Std. Error Beta

  (Constant) 108,166 5,895 18,349 ,000 jarak alat -1,031 ,104 -,733 -9,883 ,000 1 kecepatan

  ,024 ,113 ,016 ,214 ,831 kereta api

  • Kebisingan dengan Jarak penguk
  • Model Summary

  1 Regression 1540,366 1 1540,366 98,781 ,000

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

  Coefficients a

  b. Predictors: (Constant), jarak alat

  a. Dependent Variable: kebisingan kereta api

  86

  Residual 1325,474 85 15,594 Total 2865,839

  b

  ANOVA a Model Sum of Squares Df Mean Square F Sig.

  a. Dependent Variable: kebisingan kereta api

  b. Dependent Variable: kebisingan kereta api

  a. Predictors: (Constant), jarak alat

  ,537 ,532 3,9489 2,018

  a

  Durbin-Watson 1 ,733

  Std. Error of the Estimate

  Model R R Square Adjusted R Square

  

b

  1 (Constant) 109,291 2,627 41,604 ,000 jarak alat -1,031 ,104 -,733 -9,939 ,000 a. Dependent Variable: kebisingan kereta api

  • Kebisingan dengan Jenis kereta, panjang rangkaian, kecepatan kereta dan jarak pengukuran

  

b

Model Summary -

  Model R R Square Adjusted R Std. Error of the Durbin-Watson Square Estimate

  a

  1 ,741 ,549 ,527 3,9681 2,034

  a. Predictors: (Constant), panjang rangkaian, jarak alat, kecepatan kereta api, jenis kereta b. Dependent Variable: kebisingan kereta api

  a ANOVA Model Sum of Squares df Mean Square F Sig. b

  Regression 1574,662 4 393,666 25,001 ,000

  1 Residual 1291,177 82 15,746 Total 2865,839

  86

  a. Dependent Variable: kebisingan kereta api

  b. Predictors: (Constant), panjang rangkaian, jarak alat, kecepatan kereta api, jenis kereta

  a Coefficients Model Unstandardized Standardized t Sig.

  Coefficients Coefficients B Std. Error Beta

  (Constant) 110,539 7,154 15,452 ,000 jenis kereta -1,923 1,338 -,163 -1,437 ,154 jarak alat -1,031 ,104 -,733 -9,891 ,000

  1 kecepatan kereta

  • ,009 ,127 -,006 -,072 ,943 api panjang

  ,209 ,179 ,129 1,169 ,246 rangkaian a. Dependent Variable: kebisingan kereta api

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