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All Journal JSM (Jurnal SIFO Mikroskil) METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Jurnal Mantik INFOKUM
Pahala Sirait
STMIK Mikroskil
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Languange, Linguistic, Communication & Media

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Credit Card Risk Classification Using K-Nearest Neighbor Weighted Algorithm Based on Forward Selection Sartika Dewi Purba; Pahala Sirait; Arwin Arwin
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.Vol4.2020.960.pp1551-1559

Abstract

One form of credit card risk is non-performing credit cards, which describe a situation where loan repayment approval on credit cards runs the risk of failure. In the classification technique there are several algorithms that can be used, one algorithm that is often used is Weighted k-nearest neighbor (WKNN). This study aims to improve the performance of the Weighted k-nearest neighbor (WKNN) algorithm by applying the forward selection feature that is used to select each unused feature when starting a feature iteration, the results of the study show that by adding forward performance selection of the Weighted k-nearest algorithm neighbor (WKNN) get a better value that is 86.4%, compared to using the Weighted k-nearest neighbor (WKNN) algorithm without a forward selection that is equal to 60.1%.
Co-Authors Albert - Ali Akbar Lubis Andri, Andri Andrya Tanrisiono Andy - Arwin Arwin Arwin Halim Asima Rohana Bezaro Gea Felix Harmoko Lubis Irpan Pardosi Jeffry Wijaya Jontinus Manullang Kevin - Kristian Telaumbanua Luis Tono Pyter Wahyu Kosasih Ricky - Ricky Chandra Rudi Chandra Said Faisal Sartika Dewi Purba Stephen Putra Sutra Steven Goh Syanti Irviantina Theresia F M Butarbutar William Makmur Williams Chandra