Majalah Bisnis & IPTEK
Vol 16 No 1 (2023): Majalah Bisnis & IPTEK

Predicting Credit Paying Ability With Machine Learning Algorithms

Ama Febriyanti (Universitas Negeri Malang)
Tomy Rizky Izzalqurny (Universitas Negeri Malang)

Article Info

Publish Date
21 Sep 2023

Abstract

Most people still have difficulty accessing finance because of a lack or even no credit history. This study aims to develop a data model that predicts a customer's ability to pay from various aspects other than credit history. This study uses the CRSIP-DM (Cross Industry Standard Process Model for Data mining) method. The data used in this study is the Home Credit Default Risk dataset collected by documentation techniques. The data were then analyzed using data modeling analysis techniques, namely logistic regressor, decision tree classifier, random forest classifier, and lgbm classifier. This study found that the best model for predicting client payment ability is the lgbm classifier or the Random Forest Classifier.

Copyrights © 2023




Citation Download
RIS
EndNote, Reference Manager, ProCite
BibTex
Latex, Jabref
Original Source
Download Original
Google Scholar
Check in Google Scholar
Journal Info
Majalah Bisnis & IPTEK
Website

Abbrev

bistek

Publisher

Sekolah Tinggi Ilmu Ekonomi Pasundan Bandung

Subject

Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

Description

Related to the fields of Accounting and Management as well as the Context of Business and Science and Technology in Indonesia, also intended as a medium of communication between academics who are interested in business and science and technology studies from the point of view of accounting and ...