Aplikasi Prediksi Kelayakan Calon Anggota Kredit Menggunakan Algoritma Naïve Bayes

Abstract

As a financial institution other than a conventional bank, the coorperative has a role to play in overcoming the economy of the people in the regions. The event was also carried out by the Saving and Loans Cooperative Baitul Maal wa Tamwil (KSPPS BMT) "Arta Jiwa Mandiri" Wonogiri which is engaged in syariah credit and saving credit business. On proses of credit cooperative saving business cooperative have provisions in choosing a worthy member candidate to be given capital. It aims to overcome the problems such as member stuck in instalment payments. So it is necessary for an application that can prediction prospective credit members who are eligible to get loans from the cooperative with data mining techniques. Naïve Bayes algorithm is used in this case to predict the feasibility of prospective members of credit and savings loan which will include the current category, substandard or loss of time borrowing. The result of this research get Accuracy value equal to 80%, Precision value equal to 82% and Recall value equal to 94%. Therefore, this application can assist the cooperative in considering the prospective members of a decent credit to get capital.