skip to main content

KAPLAN-MEIER AND NELSON-AALEN ESTIMATORS FOR CREDIT SCORING

*Tatik Widiharih scopus  -  Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro, Indonesia
Agus Rusgiyono  -  Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro, Indonesia
Sudarno Sudarno  -  Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro, Indonesia
Bagus Arya Saputra  -  Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro, Indonesia
Open Access Copyright (c) 2023 MEDIA STATISTIKA under http://creativecommons.org/licenses/by-nc-sa/4.0.

Citation Format:
Abstract
Financial institutions use credit scoring analysis to predict the probability that a customer will default. In this paper, we determine the probability of default using nonparametric survival analysis that are Kaplan-Meier and Nelson-Aalen. The analysis is based on survival function curves, cumulative hazard function curves, mean survival time, and standard error of estimators. Based on the curves of survival function for both Kaplan Meier and Nelson Aalen estimators relatively the same. Based on the curves of cumulative hazard function, mean survival time, and standard error the Nelson-Aalen estimators are slightly higher than Kaplan-Meier.
Fulltext View|Download
Keywords: Kaplan-Meier; Nelson-Aalen; Survival Function; Cumulative Hazard Function.

Article Metrics:

  1. Ata, N. & Sozer M.T. (2007). Cox Regression Model with Nonproportional Hazard Applied to Lung Cancer Survival Data. Hacettepe Journal of Mathematics and Statistics, 36(2),157-167
  2. Collett, D. (2015). Modelling Survival Data in Medical Research second edition. Chapman and Hall/CRC, New York
  3. Jaber, J.J, Ismail, N & Ramli, S.N.M. (2017). Credit Risk Assessment Using Survival Analysis for Progressive Right-Cencored Data: a case Study in Jordan. Jurnal of Internet Banking and Commerce, 22(1), 1-18
  4. Kleinbaum, D.G & Klein, M. (2012). Survival Analysis A Self-Learning Text. Springer Science Business Media, Inc. New York
  5. Kurniawan, I, Kurnia, A & Sartono, B (2015). Survival Analysis with Extended Cox Model About Durability Debtor efforts on Credit Risk, Forum Statistika dan Komputasi: Indonesian Jurnal of Statistics, 20(2), 85-95
  6. Njomen, D.A.N, & Wandji, J.N. (2014). Nelson-Aalen and Kaplan-Meier Estimators in Completing Risks, Applied mathematics, 2014, 5, 755-766
  7. Mukid, M.A. Widiharih T. & Mustafid. (2019). An Empirical Comparison Of Some Modified Nearest Neighbor Rule For Credit Scoring Analysis: Case Study In Indonesia. Journal of Theoritical and Applied Information Technology, 97(5), 1644 - 1654
  8. Mukid, M.A. Widiharih, T. Rusgiyono A. & Prahutama A. (2018). Credit scoring analysis using k nearest neighbor. J. Phys. Conf. Ser. 1025012114, doi: 10.1088/1724-6596/1025/1/012114
  9. Mukid, M.A. & Widiharih, T. (2016). Model penilaian kredit menggunakan analisis diskriminan dengan variable bebas campuran biner dan kontinu, Media Statistika 9(2):107-118
  10. Pratiwi H., Mukid M.A., Hoyyi A., Widiharih T., 2019, Credit scoring analysis using pseudo nearest neighbor. J. Phys. Conf. Ser. 1217012100, doi: 10.1088/1724-6596/1217/1/012100
  11. Sa’diah C, Widiharih T and Hakim AR 2021 Klasifikasi pemberian kredit sepeda motor menggunakan metode regresi logistic biner dan Chi-Square Automatic Interaction Detection (CHAID) dengan GUI R, Gaussian 10(2):159-169
  12. Widiharih ,T. & Mukid, M.A. (2018). Credit Scoring Menggunakan Metode Multi Local Means Based K Harmonic Nearest Neighbor (MLMKHNN). Media Statistika, 11(2), 107 – 117
  13. Widiharih, T. Mukid, M.A.& Mustafid. (2018). Credit scoring analysis using kernel discriminant. J. Phys. Conf. Ser. 1025012124, doi: 10.1088/1742-6569/1025/1/012124
  14. Zeng, P. (2017). Survival Analysis: Nonparametric Estimation, Department of Mathematics and Statistics, Auburn University, Alabama US

Last update:

No citation recorded.

Last update: 2024-04-14 09:53:23

No citation recorded.