Article Per Year (5 Year)
p-Index From 2019 - 2024
0.23
P-Index
This Author published in this journals
All Journal Journal Sensi: Strategic of Education in Information System
Suhaepi, Muhamad Iip
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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

Found 1 Documents
Search
Journal : Journal Sensi: Strategic of Education in Information System

 1 
Credit Risk Prediction Model Using Support Vector Machine with Parameter Optimization in Banks Martono, Aris; Padeli, Padeli; Suhaepi, Muhamad Iip; Santoso, Sugeng; Sunandar, Endang
Journal Sensi: Strategic of Education in Information System Vol 10 No 2 (2024): Journal Sensi
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/sensi.v10i2.3463

Abstract

Abstract This research aims to determine the Support Vector Machine (SVM) model with Parameter Optimization in predicting loan worthiness to avoid the risk of bad credit at the Bank. Every bank tries to market financial loan products with very strict requirements. One of the requirements is that the company's financial reports must be healthy if it borrows money from a bank to develop the company's business. In the credit analysis process, there are 19 financial factors that must be measured from dozens or even hundreds of companies proposing financial loans, making it difficult for credit analysts to make decisions about whether these companies are worthy of borrowing or not. Therefore, this research was carried out by comparing the two models, namely SVM with parameter optimization and SVM with parameter optimization and Particle Swarm Optimization (PSO) to select the best model. The research results show that the Area Under Curve (AUC) criteria with validation number of folds (nof) = 10 and nof = 5 are 98.80% and 98.80%, meaning good and stable in the SVM model with parameter optimization. Meanwhile, the SVM model with parameter optimization and PSO has better AUC for validation nof=5 (99%) but for AUC with validation nof=10 (98.30%) it is less good.
Co-Authors Martono, Aris Padeli Padeli Sugeng Santoso Sunandar, Endang