RANCANG BANGUN APLIKASI PREDIKSI CALON KREDITUR PADA BANK MUAMALAT KUPANG

The implementation of stored-transaction data can provide a lot of useful knowledge to createbusinesses intelligence in Muamalat Bank. But Muamalat Bank has not done it yet; so, it will be difficultto give credits to the creditors. This study aimed to create business intelligence in terms of prospectivecreditors prediction. It was expected that it could predict creditors in making payments using old existingcreditors forms data. The research applied the K-Nearest Neighbor algorithm (K-NN) where thisalgorithm looking for similarly between render candidates and old creditors as much as k values thatstill or have done their lends to Muamalat Bank Kupang. The result of this research shows that with KNNalgorithm, a creditor can be predict using data comparism. Highest accuracy can be reach when kvalue=5, with accuracy level up to 80%