ANALISIS REGRESI KOMPONEN UTAMA UNTUK MENGATASI MASALAH MULTIKOLINIERITAS DALAM ANALISIS REGRESI LINIER BERGANDA
The climate in Ambon, are influenced by sea climate and season climate, cause of this island arrounded by sea, it is make very high rainfall intensity. A very high collinearity between independent variables, make the estimate can not rely be ordinary least square method so it market with not real re...
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| Language: | English |
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Universitas Pattimura
2012-03-01
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| Series: | Barekeng |
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| Online Access: | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/202 |
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| author | Gresyea L. Marcus Henry J. Wattimanela Yopi A. Lesnussa |
| author_facet | Gresyea L. Marcus Henry J. Wattimanela Yopi A. Lesnussa |
| author_sort | Gresyea L. Marcus |
| collection | DOAJ |
| description | The climate in Ambon, are influenced by sea climate and season climate, cause of this island arrounded by sea, it is make very high rainfall intensity. A very high collinearity between independent variables, make the estimate can not rely be ordinary least square method so it market with not real regretion coefficient and the collinearity. Collinearity can be detected by linier correlation coefficient between independent variables and also with VIF way. Regretion principal component analysis is used to remove collinearity and all of independent variable into model, this analysis is regretion analysis technique wher eare combinated with principal component analysis technique. The object of this analysis is to simplify the variable by overcast it dimension, we can do it removes the correlation between coefficient by transformation. Regresion can help to solve this case rainfall in Ambon on 2010. So the colinearity to independent variables can be overcome and then we can get the best regretion rutes. |
| format | Article |
| id | doaj-art-3bce1c607a0446cc96df6ba51233f9bb |
| institution | Kabale University |
| issn | 1978-7227 2615-3017 |
| language | English |
| publishDate | 2012-03-01 |
| publisher | Universitas Pattimura |
| record_format | Article |
| series | Barekeng |
| spelling | doaj-art-3bce1c607a0446cc96df6ba51233f9bb2025-08-20T03:36:13ZengUniversitas PattimuraBarekeng1978-72272615-30172012-03-0161314010.30598/barekengvol6iss1pp31-40202ANALISIS REGRESI KOMPONEN UTAMA UNTUK MENGATASI MASALAH MULTIKOLINIERITAS DALAM ANALISIS REGRESI LINIER BERGANDAGresyea L. Marcus0Henry J. Wattimanela1Yopi A. Lesnussa2Jurusan Matematika FMIPA Universitas PattimuraJurusan Matematika FMIPA Universitas PattimuraJurusan Matematika FMIPA Universitas PattimuraThe climate in Ambon, are influenced by sea climate and season climate, cause of this island arrounded by sea, it is make very high rainfall intensity. A very high collinearity between independent variables, make the estimate can not rely be ordinary least square method so it market with not real regretion coefficient and the collinearity. Collinearity can be detected by linier correlation coefficient between independent variables and also with VIF way. Regretion principal component analysis is used to remove collinearity and all of independent variable into model, this analysis is regretion analysis technique wher eare combinated with principal component analysis technique. The object of this analysis is to simplify the variable by overcast it dimension, we can do it removes the correlation between coefficient by transformation. Regresion can help to solve this case rainfall in Ambon on 2010. So the colinearity to independent variables can be overcome and then we can get the best regretion rutes.https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/202rainfall, principal component, ordinary least square, colinearty, regretion |
| spellingShingle | Gresyea L. Marcus Henry J. Wattimanela Yopi A. Lesnussa ANALISIS REGRESI KOMPONEN UTAMA UNTUK MENGATASI MASALAH MULTIKOLINIERITAS DALAM ANALISIS REGRESI LINIER BERGANDA Barekeng rainfall, principal component, ordinary least square, colinearty, regretion |
| title | ANALISIS REGRESI KOMPONEN UTAMA UNTUK MENGATASI MASALAH MULTIKOLINIERITAS DALAM ANALISIS REGRESI LINIER BERGANDA |
| title_full | ANALISIS REGRESI KOMPONEN UTAMA UNTUK MENGATASI MASALAH MULTIKOLINIERITAS DALAM ANALISIS REGRESI LINIER BERGANDA |
| title_fullStr | ANALISIS REGRESI KOMPONEN UTAMA UNTUK MENGATASI MASALAH MULTIKOLINIERITAS DALAM ANALISIS REGRESI LINIER BERGANDA |
| title_full_unstemmed | ANALISIS REGRESI KOMPONEN UTAMA UNTUK MENGATASI MASALAH MULTIKOLINIERITAS DALAM ANALISIS REGRESI LINIER BERGANDA |
| title_short | ANALISIS REGRESI KOMPONEN UTAMA UNTUK MENGATASI MASALAH MULTIKOLINIERITAS DALAM ANALISIS REGRESI LINIER BERGANDA |
| title_sort | analisis regresi komponen utama untuk mengatasi masalah multikolinieritas dalam analisis regresi linier berganda |
| topic | rainfall, principal component, ordinary least square, colinearty, regretion |
| url | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/202 |
| work_keys_str_mv | AT gresyealmarcus analisisregresikomponenutamauntukmengatasimasalahmultikolinieritasdalamanalisisregresilinierberganda AT henryjwattimanela analisisregresikomponenutamauntukmengatasimasalahmultikolinieritasdalamanalisisregresilinierberganda AT yopialesnussa analisisregresikomponenutamauntukmengatasimasalahmultikolinieritasdalamanalisisregresilinierberganda |