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All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan
Sitti Nurhaliza
Department of Statistics, Faculty of Mathematics and Natural Sciences, Bogor Agricultural University
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation

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A COMPARISON OF COX PROPORTIONAL HAZARD AND RANDOM SURVIVAL FOREST MODELS IN PREDICTING CHURN OF THE TELECOMMUNICATION INDUSTRY CUSTOMER Sitti Nurhaliza; Kusman Sadik; Asep Saefuddin
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 4 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (398.623 KB) | DOI: 10.30598/barekengvol16iss4pp1433-1440

Abstract

The Cox Proportional hazard model is a popular method to analyze right-censored survival data. This method is efficient to use if the proportional hazard assumption is fulfilled. This method does not provide an accurate conclusion if these assumptions are not fulfilled. The new innovative method with a non-parametric approach is now developing to predict the time until an event occurs based on machine learning techniques that can solve the limitation of CPH. The method is Random Survival Forest, which analyzes right-censored survival data without regard to any assumptions. This paper aims to compare the predictive quality of the two methods using the C-index value in predicting right-censored survival data on churn data of the telecommunication industry customers with 2P packages consisting of Internet and TV, which are taken from all customer databases in the Jabodetabek area. The results show that the median value of the C-index of the RSF model is 0.769, greater than the median C-index value of the CPH model of 0.689. So the prediction quality of the RSF model is better than the CPH model in predicting the churn of the telecommunications industry customer.
Co-Authors Asep Saefuddin Kusman Sadik