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All Journal E-Journal Home Economic and Tourism Primary: Jurnal Pendidikan Guru Sekolah Dasar JURNAL TUGAS AKHIR MAHASISWA Jurnal Pustaka Ilmiah Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences JIEP: Jurnal Ilmu Ekonomi dan Pembangunan Proceeding International Seminar of Islamic Studies Kode : Jurnal Bahasa JURNAL MUARA PENDIDIKAN TARBIYAH DARUSSALAM: JURNAL ILMIAH KEPENDIDIKAN DAN KEAGAMAAN JURSIMA Jurnal Sistem Informasi dan Manajemen
Rahimah Rahimah
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Religion Arts Humanities Astronomy Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Physics Social Sciences Other

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Journal : Jurnal Sistem Informasi dan Manajemen

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ANALISA RISIKO KREDIT MACET DENGAN PENDEKATAN DATA MINING (STUDI KASUS: KOPERASI PUTRA KEMBAR) Widya Lelisa Army; Widya Jati Lestari; Rahimah Rahimah; Dedi Rahman Habibie
JURSIMA Vol 9 No 1 (2021): Jursima Vol. 9 No. 1, April Tahun 2021
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v9i1.241

Abstract

Data mining is a form of development of computerized methods that are widely used in various fields, especially those related to data. Data mining has the main function of turning data that seems meaningless into very valuable information. The use of data mining in credit risk analysis is very feasible to implement, one of the reasons is that data mining is able to recognize customer credit patterns originating from past data, resulting in information in the form of knowledge that can facilitate credit analysts in carrying out their duties. The purpose of this research is to simplIFy the task of credit analysts AND minimize misjudgment of prospective customers AND also shorten the time of assessment AND with accurate AND fast decision results. The assessment is carried out by utilizing past data based on predetermined criteria, THEN the data will be processed using the data mining method, namely the c4.5 algorithm. The results of the research are in the form of a knowledge rule: R1: IF Loan Amount = Small THEN Performing Loan (PL), R2: IF Loan Amount = Big THEN Non-Performing Loan (NPL), R3: IF Loan Amount = Medium AND Work= Employee THEN Performing Loan (PL), R4: IF Loan Amount = Medium AND Work=Entrepreneurial THEN Performing Loan (PL), R5: IF Loan Amount = Medium AND Work= PNS THEN Non-Performing Loan. From testing the new data testing with the value of Work ‘Employee’ Loan Amount ‘Rp. 7.000.000,-’ dependents ‘2’ length of loan ‘24 months’ with the results of the decision ‘Performing Loan (PL)’ . The result of the decision is based on the rule, namely R4: IF Loan Amount = Medium AND Work=Entrepreneurial THEN Performing Loan (PL).
Co-Authors Anni Faridah Asmar Yulastri Dedi Rahman Habibie Evicenna Yuris Fitri Hidayati Hasibuan I Nyoman Adi Putra Ika Chandriyanti Khairina Nasution Muzdhalifah Muzdhalifah Nazwa Mustika Qaulan Raniyah Sabhan Sabhan T. Thyrhaya Zein Widya Jati Lestari Widya Lelisa Army