Metode Regresi Ridge Untuk Mengatasi Kasus Multikolinear

Authors

  • Margaretha Ohyver Bina Nusantara University

DOI:

https://doi.org/10.21512/comtech.v2i1.2782

Keywords:

multicolinear, Ridge regression

Abstract

Multicolinear is a case that occurs in multi-linear regression analysis. Using multicolinear, it will be difficult to separate the influence of each independent variable towards the response variables. It also occurs in a farm production like cabbage. To solve this problem, Ridge regression method is used. This research aims to obtain a Ridge regression model to solve the multicolinear case. By using this method, the alleged regression coefficient is obtained by variance inflation factor less than ten for six free variables.

 

Dimensions

Plum Analytics

References

Haerunissa. (2004), Penggunaan Metode Regresi Komponen Utama pada Kasus Data yang Memiliki Kasus Kolinear Ganda. Skripsi S1. Kendari: Jurusan Matematika, FMIPA Universitas Haluoleo.

Hoerl, A. E., and Kennard, R. W. (1970). Ridge Regression: Biased Estimation for Nonorthogonal Problems. A Journal of Statistics for the Physical Chemical and Engineering Sciences, 12 (1), 55-67.

Rietveld, P., dan Sunaryanto, L. T. (1994). 87 Kasus Pokok dalam Regresi Berganda (edisi pertama). Yogyakarta: Andi Offset.

Ryan, T. P. (1997). Modern Regression Method. New York: Wiley.

Supranto, J. (1986). Pengantar Probabilita dan Statistik Induktif (edisi pertama). Jakarta: Erlangga.

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Published

2011-06-01

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