DOI: https://doi.org/10.14710/medstat.17.2.117-127

EXPLORE THE DETERMINANTS OF CUSTOMERS TIME TO PAY HOUSE OWNERSHIP LOAN ON DATA WITH HIGH MULTICOLLINEARITY WITH PCA-COX REGRESSION

*Rangga Ramadhan  -  Department of Statistics, Faculty of Mathematics and Natural Sciences, Brawijaya University, Malang, Indonesia
Adfi Bio Fimba  -  Department of Statistics, Faculty of Mathematics and Natural Sciences, Brawijaya University, Indonesia
Adji Achmad Rinaldo Fernandes  -  Department of Statistics, Faculty of Mathematics and Natural Sciences, Brawijaya University, Malang, Indonesia
Solimun Solimun  -  Department of Statistics, Faculty of Mathematics and Natural Sciences, Brawijaya University, Malang, Indonesia
Fachira Haneinanda Junianto  -  Department of Statistics, Faculty of Mathematics and Natural Sciences, Brawijaya University, Malang, Indonesia
Devi Veda Amanda  -  Department of Statistics, Faculty of Mathematics and Natural Sciences, Brawijaya University, Malang, Indonesia
Rauzan Sumara  -  Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland
Open Access Copyright (c) 2024 MEDIA STATISTIKA under http://creativecommons.org/licenses/by-nc-sa/4.0.

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Abstract
One of the models in survival analysis is the Cox proportional hazards model. This method ignores assumptions regarding the distribution of survival times studied. If there are indications of multicollinearity in data handling, one way that can be done is to use PCA (Principal Component Analysis). PCA-Cox regression is a combination of survival analysis and PCA which can be an alternative in analyzing multicollinearity survival data. The large number of cases of bad credit means that customers must be careful in providing credit to prospective customers. Character, capacity, capital and collateral variables are thought to influence the length of time customers pay house ownership loans at the bank. The data used is secondary data (n=100) regarding the assessment of character variables, capacity, capital and collateral, credit collectibility, and time to pay customer house ownership loans at the bank. The results of the analysis using PCA-Cox regression show that the variables character, capacity, capital and collateral have a significant effect on the length of house ownership loan payment time for Bank X customers. The originality of this research is the use of the PCA-Cox regression integration model in bank credit risk analysis.
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Keywords: Survival Analysis; Credit Collectability; PCA; Time to Pay Credit

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