@thesis{thesis,
		author={Haris  Abdul and KUSUMA  INDAH PRADANA and Wulandari  Dewi Arianti},
		title ={KLASIFIKASI DATA PENENTUAN PENERIMAAN KREDIT PADA NASABAH KOPERASI MENGGUNAKAN ALGORITMA NAIVE BAYES (Studi Kasus : Koperasi Amanah Islamiyah)},
		year={2018},
		url={http://156.67.221.169/4607/},
		abstract={The granting of credit to the customer is an activity that has a high
degree of risk. In practice, the troubled credit often occurs due to the credit
analysis are not careful or less closely in the process of granting credit. To
prevent the occurrence of problematic credits, then required the existence of
accurate forecasting to determine the classification of granting credit to
customers, one of which uses the technology of data mining. In this study data
analyzed using naive bayes method algotitma as the process in which the
determination of the customer's credit. Naive Bayes is one method that aims to
do a classification of a particular class, then the patterns can be used to classify
the determination of credit, so that officers can more easily analyze the data
application. The results of the hypothesis or events can be estimated based on
observable evidence. The results of this research have an accuracy of 70%.}
		}