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All Journal Paradigma SPEED - Sentra Penelitian Engineering dan Edukasi
Syaifur Rahmatullah
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Computer Science & IT Education Electrical & Electronics Engineering Engineering Library & Information Science

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Journal : Paradigma

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KOMPARASI ALGORITMA C4.5 DAN SVM BERBASIS PARTICLE SWARM OPTIMAZATION DALAM PENENTUAN KREDIT Syaifur Rahmatullah
Paradigma Vol 18, No 1 (2016): Periode Maret
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (465.714 KB) | DOI: 10.31294/p.v18i1.877

Abstract

Bad credit is one of the credit risk faced by the financial and banking industry. Bad credit happens if in the long run, financial institutions or banks can not attract loans within a predetermined time. Bad credit has a negative effect on credit providers in the form of risk of loss course this should not be allowed to drag on and had to find a way out. However, to ensure accuracy in the determination of credit worthiness required an accurate algorithm. Therefore, there should be a study that aims to find an algorithm that accurately by means mengkomparasi some of them C4.5 algorithm, and SVM. To further improve the accuracy of the algorithms are in Particle Swarm Optimization with Optimazation. Berupan confusion matrix research results prove the accuracy of Support Vector Machine-based Particle Swarm Optimazation exists at the level of accuracy of 96.20% and the AUC by 0989.
Co-Authors Ade Suryanto Dini Silvi Purnia, Dini Silvi