PENERAPAN DATA MINING UNTUK MEMPREDIKSI PERILAKU NASABAH KREDIT: STUDI KASUS BPR MARCORINDO PERDANA CIPUTAT

Syaiful Anwar

Abstract


Rural Bank one of the institutions about providing loans to certain conditions and criteria. Credit
Analysis takes time and funds are not cheap so we need an appropriate method for analyzing
prospective credit customers.Data Mining is one method that can be used to analyze existing data
chunks that can be used to summarize the data provide specific information related to the data.
Data Mining classification of a decision tree algorithm C4.5 is used in forming the rules of the
statement. Decision tree model was able to improve the accuracy in analyzing the credit
worthiness of the proposed prospective credit customers. The richer the information or knowledge
contained by the training data, the accuracy of the decision tree will increase. And implementation
can be done using one of the Visual Basic programming language.

Keywords: credit customer behavior, Data Mining, C4.5 Algorithm


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DOI: https://doi.org/10.31294/p.v15i1.2197

ISSN2579-3500

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