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All Journal FORUM STATISTIKA DAN KOMPUTASI dCartesian: Jurnal Matematika dan Aplikasi Jurnal TIMES JURNAL LPPM BIDANG SAINS DAN TEKNOLOGI Jurnal Teknik Informatika (JUTIF) Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Operations Research: International Conference Series Jurnal Ilmiah Sains Journal of Information Technology, Software Engineering and Computer Science d'Cartesian: Jurnal Matematika dan Aplikasi Jurnal Informatika dan Rekayasa Perangkat Lunak
Deiby T Salaki
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Mathematics Physics

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Journal : Operations Research: International Conference Series

 1 
Comparison of Partial Least Squares Regression and Principal Component Regression for Overcoming Multicollinearity in Human Development Index Model Samosir, Ravika Dewi; Salaki, Deiby Tineke; Langi, Yohanes
Operations Research: International Conference Series Vol. 3 No. 1 (2022): Operations Research International Conference Series (ORICS), March 2022
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v3i1.126

Abstract

One of the assumptions in ordinary least squares (OLS) in estimating regression parameter is lack of multicollinearity. If the multicollinearity exists, Partial Least Square (PLS) and Principal Component Regression (PCR) can be used as alternative approaches to solve the problem. This research intends to compare those methods in modeling factors that influence the Human Development Index (HDI) of North Sumatra Province in 2019 obtained from the Central Bureau of Statistics. The result indicates that the PLS outperforms the PCR in term of  the coefficient of determination and squared error
Comparing the Performance of Prediction Model of Ridge and Elastic Net in Correlated Dataset Bastiaan, Richy Marcelino; Salaki, Deiby Tineke; Hatidja, Djoni
Operations Research: International Conference Series Vol. 3 No. 1 (2022): Operations Research International Conference Series (ORICS), March 2022
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v3i1.127

Abstract

Multicollinearity refers to a condition where high correlation between independent variables in linear regression model occurs.  In this case, using ordinary least squares (OLS) leads to unstable model. Some penalized regression approaches such as ridge and elastic-net regression can be applied to overcome the problem. Penalized regression estimates model by adding a constrain on the size of parameter regression. In this study, simulation dataset is generated, comprised of 100 observation and 95 independent variables with high correlation. This empirical study shows that elastic-net method outperforms the ridge regression and OLS.  In correlated dataset, the OLS is failed to produce a prediction model based on mean squared error (MSE)
Co-Authors Aditya Lapu Kalua Alfonsius, Eric Altien J Rindengan Anang Kurnia Angelina Monica Gulla Arief Gusnanto Bagus Sartono Bastiaan, Richy Marcelino Djoni Hatidja Eliasta Ketaren, Eliasta Faranika Deysi G Maneking Ferelda Pasriyane Kele Gloria Rompas Hamel, Jeliana Hanny A. H. Komalig Hanny Andrea Huibert Komalig Hanny Komalig I Wayan Mangku Islam, Noorul Jantje D. Prang Jantje D. Prang John S. Kekenusa Komalig, Hanny Andrea Huibert Latumakulita, Luther Aleander Lengkong, Agnes Gratia Maingga, Dikky Malvino Mait, Yeremia Armstrong Majore, Marzena Maneking, Faranika Deysi G Marline Paendong Marzena Majore Ramengkomole, Virgini Graditya Samosir, Ravika Dewi Sanriomi Sintaro Tohap Manurung Tohap Manurung Veronika H Wawo, Rohelio Yoel Yeremia Armstrong Mait Yohanes Langi