Unstable economic conditions require Bank must be careful in deciding towards lending customers. Banks should not take the risk of giving loans to customers who cannot afford to pay. This study aims to assist bank in predicting lending. The study was conducted at the Bank Perkreditan Rakyat in Medan. The study was conducted applying data mining using the nearest neighbor algorithm. This algorithm was chosen because the nearest neighbor can calculate the closeness between new cases and old cases based on matching weights from a number of existing features. This algorithm will calculate the closeness with predetermined criteria. Hoped bank will be helped in making predictions.
Private or public companies need tools to make easy decision making process. This research conducted at PT. FIF Medan. Focus in decision making to provision motor vehicle loans. The study do because PT. FIF Medan has problems to determining whether consumers are given financing. Research using Back Propagation Neural Network. Back Propagation Neural Network is a method that simplifies complex problems. Simplifying model by taking the most essential core issues. Research will be carried out with the stages of identifying problems, determining needs, analyzing, and choosing alternatives. 8 (eight) criteria will be parameters, including the amount of dependents, length of work, home status, history of finance, employee workplace, vehicle type, financing tenure, and monthly income.
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