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Lembaga Penelitian Pengabdian Masyarakat Universitas Nusa Mandiri
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EVALUASI PENENTUAN KELAYAKAN PEMBERIAN KREDIT KOPERASI SYARIAH MENGGUNAKAN ALGORITMA KLASIFIKASI C4.5
Keywords:
Algoritma C4.5, Kredit, Koperasi Syariah
Abstract
Credit is the provision of money or bills that can be equivalent, based on the approval of borrowing between banks and other parties that requires the borrower to pay off their debts after a certain period of time with interest. While the cooperative is a business entity consisting of one person or legal entity with bases its activities based on the principle of cooperation as well as driving people's economy based on the principle of kinship. And to Cooperative Financial Services, hereinafter referred Syariah is a cooperative whose main business is engaged in financing, investments, and deposits according to the pattern of results (sharia). In analyzing a credit analyst sometimes an inaccurate analysis, so there are some customers who are less capable of performing loan payments, resulting in bad credit. Many studies using the C4.5 algorithm for the determination of creditworthiness, but the resulting accuracy is less accurate. After testing the two models namely algorithm C4.5 the results obtained are the C4.5 algorithm produces an accuracy value by 88% and the AUC value of 0.898 with the diagnosis of Good Classification.
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References
Bastos, J. A. (2008). Credit Scoring with Boosted Decision Trees. MPRA , hal 1- 13.
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Gorunescu, F. (2011). Data Mining Concepts, Model and Techniques. Berlin: Springer.
Han, J., & Kamber, M. (2006). Data Mining Concepts and Techniques. San Francisco: Diane Cerra.
Jiang, Y. (2009). Credit Scoring Model Based on the Decision Tree and the Simulated Annealing Algorithm. 2009 World Congress on Computer Science and Information Engineering (hal. 18 - 22). Los Angeles: IEEE Computer Society.
Larose, D. T. (2005). Discovering Knowledge In Data. Canada: Wiley- Interscience.
Rapid-I. (2010). Rapid Miner User Manual . Rapid-I.
Sugiyono. (2002). Metode Penelitian Bisnis. Bandung: CV. Alfabeta.
Susanto, S., & Suryadi, D. (2010). Pengantar Data Mining menggali Pengetahuan dari Bongkahan Data. Yogyakarta: C.V ANDI OFFSET.
UndangUndang Perbankan No.10 Tahun 1998.
Yu, L., Chen, G., Koronios, a., Zhu, S., & Guo, X. (2007). Application and Comparison of Classification Techniques in Controlling Credit Risk. World Scientific , 111.
Zurada, J. (2010). Could decision trees improve the classification accuracy and interpretability of loan granting decision? 43rd Hawaii International Conference on System Sciences (pp. 1-9).
Published
2015-03-07
How to Cite
Masripah, S. (2015). EVALUASI PENENTUAN KELAYAKAN PEMBERIAN KREDIT KOPERASI SYARIAH MENGGUNAKAN ALGORITMA KLASIFIKASI C4.5. Jurnal Pilar Nusa Mandiri, 11(1), 1-10. Retrieved from https://ejournal.nusamandiri.ac.id/index.php/pilar/article/view/407
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