Sistem Klasifikasi Kelayakan Debitur Lembaga Perkreditan Desa Menggunakan Algoritma C4.5 dan Bagging
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Authors:
Ni Putu Novia Ardiyanti, Made Agung Raharja, Luh Gede Astuti, I Komang Ari Mogi, Luh Arida Ayu Rahning Putri, I Dewa Made Bayu Atmaja Darmawan
Abstract:
“LPD Penarukan is one of the financial institutions that provides credit loans to people in the Penarukan traditional village area, Bali Province. This study aims to assist credit officers in classifying loans submitted by prospective debtors based on analysis of character, capacity, capital, collateral, and economic conditions by developing a credit classification system with a case study on LPD Penarukan using the C4.5 algorithm with bagging technique. Based on the results of research and testing that have been carried out, the system built is able to carry out the process of classifying credit data indicated by the results of usability testing giving the learnability component has an average value of 78.2%, the memorability component has an average value of 74.07%. The efficiency component gets an average value of 83.70%, the error component gets an average of 82.22%, the satisfaction component gets an average value of 83.89%. Tests were also carried out by calculating the accuracy and F1 score using the C4.5 algorithm with the bagging technique which resulted in an accuracy value of 81.87% and an F1 score of 89.62%.”
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https://jurnal.harianregional.com/jlk/full-89014
Published
2022-07-15
How To Cite
ARDIYANTI, Ni Putu Novia et al. Sistem Klasifikasi Kelayakan Debitur Lembaga Perkreditan Desa Menggunakan Algoritma C4.5 dan Bagging.JELIKU (Jurnal Elektronik Ilmu Komputer Udayana), [S.l.], v. 11, n. 3, p. 607-616, july 2022. ISSN 2654-5101. Available at: https://ojs.unud.ac.id/index.php/JLK/article/view/89014. Date accessed: 02 Jun. 2025. doi:https://doi.org/10.24843/JLK.2023.v11.i03.p17.
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Issue
Vol 11 No 3 (2023): JELIKU Volume 11 No 3, February 2023
Section
Articles
Copyright
This work is licensed under a Creative Commons Attribution 4.0 International License
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