PREDIKSI NASABAH KREDIT USAHA RAKYAT MENGGUNAKAN ALGORITMA C4.5

yadi yadi

Abstract


Banking is a financial institution that collects all public funds in the form of deposits and manages these funds to maintain liquidity and security in processing funds aimed at maximizing profits. Banks must provide financial traffic services needed by all customers for both internal and external transactions. Some programs offered by banks in providing financial services include the provision of micro-business credit (KUR) aimed at improving the community's economy. However, the problem that arises in the potential provision of KUR assistance is that it often misses the target, resulting in many customers not optimally receiving financial services. C4.5 Algorithm is an accurate data mining method used for data prediction and processing for decision making. This research aims to predict banking customers in providing KUR using the C4.5 algorithm. The methodology used is the Cross-Industry Standard Process Model for Data Mining, employing the C4.5 algorithm. The prediction results of micro-business credit recipients using the C4.5 algorithm are excellent, as seen from the calculation of entropy value of 0.97 and gain value of 0.69, as well as the formation of decision trees with several determinant data sets such as data from the Ministry of Home Affairs, OJK's Slik, repayment capacity, types of businesses, and locations. The optimization of the C4.5 algorithm in data processing helps in determining customers more optimally, reducing mis-targeted micro-business credit assistance.

Keywords: Customer, Algorithm C4.5, Data mining


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References


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DOI: https://doi.org/10.21107/nero.v9i1.25348

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