Implementation of Tsukamoto Fuzzy Inference System on Loan Eligibility Determination

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Artikel (Bahasa Indonesia)
Published Dec 16, 2024
DOI : https://doi.org/10.32664/smatika.v14i02.1463
  • Halaman : 399 - 408
  • Abstract views : 14
  • PDF views : 4

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Evi Nur Hidayah
Informatika, Universitas Teknologi Yogyakarta, Indonesia
Sulistyo Dwi Sancoko
Informatika, Universitas Teknologi Yogyakarta, Indonesia

Abstract

Loans are an important financial instrument in modern life for both individuals and business groups. Consideration of prospective borrowers is very important to reduce the risk of default. However, in Gapoktan Makmur Sejahtera the consideration process is still done manually. Therefore, it is necessary to develop a more systematic and measurable approach in assessing the feasibility of granting loans to minimize the risk of default. The data source of this research comes from loan data at the Makmur Sejahtera Farmer Group Association (Gapoktan). This research uses the Tsukamoto Fuzzy Inference System (FIS) method with 3 input variables, namely income, collateral, and character of prospective borrowers. The output variable in this study is eligibility in the form of a percentage of the results of the FIS Tsukamoto calculation. The application in this study was developed with the Python programming language and the Flask framework. The database used in this research is MySQL. The results showed that the application of determining the feasibility of granting loans was successfully made and could help in the process of determining prospective borrowers at Gapoktan Makmur Sejahtera so as to reduce the risk of default.

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Issue
Vol 14 No 02 (2024): SMATIKA Jurnal : STIKI Informatika Jurnal
Section
Articles
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