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

Syaiful Anwar (Program Studi Manajemen Informatika Akademik Manajemen Informatika dan Komputer Bina Sarana Informatika (AMIK BSI) Jl. Banten No.1 Karawang)

Paradigma
Vol 15, No 1 (2013): Periode Maret 2013

Rural Bank one of the institutions about providing loans to certain conditions and criteria. CreditAnalysis takes time and funds are not cheap so we need an appropriate method for analyzingprospective credit customers.Data Mining is one method that can be used to analyze existing datachunks 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 thestatement. Decision tree model was able to improve the accuracy in analyzing the creditworthiness of the proposed prospective credit customers. The richer the information or knowledgecontained by the training data, the accuracy of the decision tree will increase. And implementationcan be done using one of the Visual Basic programming language.Keywords: credit customer behavior, Data Mining, C4.5 Algorithm