Article Per Year (5 Year)
p-Index From 2019 - 2024
0.23
P-Index
This Author published in this journals
All Journal JURIKOM (Jurnal Riset Komputer)
Dwi Sidik Permana
Institut Bisnis & Informatika Kosgoro 1957, Jakarta Selatan
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Prediksi Tingkat Risiko Kredit dengan Data Mining Menggunakan Algoritma Decision Tree C.45 Nurdiana Handayani; Herry Wahyono; Joko Trianto; Dwi Sidik Permana
JURIKOM (Jurnal Riset Komputer) Vol 8, No 6 (2021): Desember 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v8i6.3643

Abstract

Finance companies in providing credit conduct data analysis first to reduce credit risk. When customers do not pay credit smoothly, it will harm the company. For this reason, credit analysis is an important factor to minimize financial risk. So, it takes a predictive analysis of the level of credit risk based on data or files from customers. This study aims to predict the level of credit risk with data mining using the C.45 decision tree algorithm. There are two classes of risk level predictions, namely current and non-current. The C.45 decision tree algorithm has a function to find knowledge or patterns of characteristic similarity in a particular group or class. In this study, the C.45 algorithm was implemented and analyzed using the WEKA application. From the results of the evaluation using the confusion matrix, the accuracy generated for 1,153 training data with 91 testing data and the six attributes used produces an accuracy of 79%
Co-Authors Herry Wahyono Joko Trianto Nurdiana Handayani