Article Per Year (5 Year)
p-Index From 2020 - 2025
0.408
P-Index
This Author published in this journals
All Journal Jurnal Mantik BERNAS: Jurnal Pengabdian Kepada Masyarakat
Ellisa Purba
STMIK Pelita Nusantara
Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Dentistry Economics, Econometrics & Finance Education Environmental Science Languange, Linguistic, Communication & Media Mathematics Neuroscience Nursing Public Health Social Sciences Veterinary Other

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Jurnal Mantik

 1 
Classification of Feasibility of Credit for Candidated CS Finance Debtors Using Naïve Bayes Method Nuraisana; Ellisa Purba
Jurnal Mantik Vol. 4 No. 3 (2020): November: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.Vol4.2020.1031.pp1885-1899

Abstract

CS Finance is one of the central financing institutions in the two-wheeler finance industry. CS Finance, which was founded in 2010 under the name PT Central Santosa Finance. The problem that is often faced is when conducting administrative assessments to determine the right prospective debtor's eligibility. We need a system that can assist CS Finance in determining the feasibility of prospective debtors quickly and precisely. The method used in this research is Naïve Bayes. The data processed is data of prospective debtors. The variables used have been determined based on four attributes, namely character, capacity, capital, and conditions; testing is carried out using Rapidminer software, and the accuracy of the Naïve Bayes algorithm for predicting the feasibility of prospective debtors based on training data shows good performance, namely 80%. Hence, it is feasible for use. To make it easier for users to predict prospective borrowers' creditworthiness, a creditworthiness classification system for prospective debtors has been created in CS Finance using the web-based naïve Bayes method.
Co-Authors Nuraisana Nuraisana Wira Apriani