Naïve Bayes, Decision Tree, and SVM Algorithm for Classification of Sharia Cooperative Customer Financing Approval

The decision on financing approval in sharia cooperatives has a high risk of the inability of customers to pay their credit obligations at maturity or referred to as bad credit. To maintain and minimize risk, an accurate method is needed to determine the financing agreement. The purpose of this stud...

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Published in:Jurnal Teknologi dan Sistem Komputer
Main Authors: Nurajijah Nurajijah, Dwiza Riana
Format: Article
Language:English
Published: Diponegoro University 2019-04-01
Subjects:
Online Access:https://jtsiskom.undip.ac.id/index.php/jtsiskom/article/view/13251
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author Nurajijah Nurajijah
Dwiza Riana
author_facet Nurajijah Nurajijah
Dwiza Riana
author_sort Nurajijah Nurajijah
collection DOAJ
container_title Jurnal Teknologi dan Sistem Komputer
description The decision on financing approval in sharia cooperatives has a high risk of the inability of customers to pay their credit obligations at maturity or referred to as bad credit. To maintain and minimize risk, an accurate method is needed to determine the financing agreement. The purpose of this study is to classify sharia cooperative loan history data using the Naïve Bayes algorithm, Decision Tree and SVM to predict the credibility of future customers. The results showed the accuracy of Naïve Bayes algorithm 77.29%, Decision Tree 89.02% and the highest Support Vector Machine (SVM) 89.86%.
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spelling doaj-art-e6c143ff2f314dddad57529331adbf252025-08-19T23:51:25ZengDiponegoro UniversityJurnal Teknologi dan Sistem Komputer2338-04032019-04-0172778210.14710/jtsiskom.7.2.2019.77-8212778Naïve Bayes, Decision Tree, and SVM Algorithm for Classification of Sharia Cooperative Customer Financing ApprovalNurajijah Nurajijah0https://orcid.org/0000-0002-6409-876XDwiza Riana1https://orcid.org/0000-0002-5072-853XProgram Studi Magister Ilmu Komputer, STMIK Nusa Mandiri, IndonesiaProgram Studi Magister Ilmu Komputer, STMIK Nusa Mandiri, IndonesiaThe decision on financing approval in sharia cooperatives has a high risk of the inability of customers to pay their credit obligations at maturity or referred to as bad credit. To maintain and minimize risk, an accurate method is needed to determine the financing agreement. The purpose of this study is to classify sharia cooperative loan history data using the Naïve Bayes algorithm, Decision Tree and SVM to predict the credibility of future customers. The results showed the accuracy of Naïve Bayes algorithm 77.29%, Decision Tree 89.02% and the highest Support Vector Machine (SVM) 89.86%.https://jtsiskom.undip.ac.id/index.php/jtsiskom/article/view/13251data miningnaive bayesdecision treesvmpembiayaan kredit
spellingShingle Nurajijah Nurajijah
Dwiza Riana
Naïve Bayes, Decision Tree, and SVM Algorithm for Classification of Sharia Cooperative Customer Financing Approval
data mining
naive bayes
decision tree
svm
pembiayaan kredit
title Naïve Bayes, Decision Tree, and SVM Algorithm for Classification of Sharia Cooperative Customer Financing Approval
title_full Naïve Bayes, Decision Tree, and SVM Algorithm for Classification of Sharia Cooperative Customer Financing Approval
title_fullStr Naïve Bayes, Decision Tree, and SVM Algorithm for Classification of Sharia Cooperative Customer Financing Approval
title_full_unstemmed Naïve Bayes, Decision Tree, and SVM Algorithm for Classification of Sharia Cooperative Customer Financing Approval
title_short Naïve Bayes, Decision Tree, and SVM Algorithm for Classification of Sharia Cooperative Customer Financing Approval
title_sort naive bayes decision tree and svm algorithm for classification of sharia cooperative customer financing approval
topic data mining
naive bayes
decision tree
svm
pembiayaan kredit
url https://jtsiskom.undip.ac.id/index.php/jtsiskom/article/view/13251
work_keys_str_mv AT nurajijahnurajijah naivebayesdecisiontreeandsvmalgorithmforclassificationofshariacooperativecustomerfinancingapproval
AT dwizariana naivebayesdecisiontreeandsvmalgorithmforclassificationofshariacooperativecustomerfinancingapproval