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Predicting the loan risk towards new customer applying data mining using nearest neighbor algorithm

S Samsir, S Suparno, Muhammad Giatman

2020IOP Conference Series Materials Science and Engineering18 citationsDOIOpen Access PDF

Abstract

Abstract 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.

Topics & Concepts

Closenessk-nearest neighbors algorithmLoanData miningMatching (statistics)Computer scienceAlgorithmFinanceBusinessArtificial intelligenceMathematicsStatisticsMathematical analysisData Mining and Machine Learning ApplicationsFinancial Distress and Bankruptcy PredictionImbalanced Data Classification Techniques