PENERAPAN NAÏVE BAYES UNTUK PREDIKSI KELAYAKAN KREDIT

Abstract

In banking business, lending a money is a routine that consists of high risks. By giving a lend to a person, a bank or an organization that have authority to to do that can lead to a bad credit because of a bad or recklessness indata analysis. In order to prevent these things to occur, a good forecasting tool is needed. The using of data mining techniques in searching process of a huge amount of data to extract information can be done quickly in order to find a good prediction of money lending, and also to find unusual patterns that cannot be seen before. Naïve Bayes can predict probability based on previous experiences (data) by studying hypothesis as the target of the classification and evidence as input features in classification model. The implemented data mining application can be used as a tool to predict the creditworthiness of a prospective borrower.