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.

Technology development makes everything unlimited. Everyone easily to gets information. There are negative and positive impacts. The one negative impact is plagiarism the work of others. Of course this brings a bad impact. This study aims to examine the similarity of Student Final Reports at the Politeknik Unggul LP3M Medan. The method used is the Cosine Similarity Method. This method was chosen because it works based on mathematical calculations. How it works is by comparing the final project done by students with the final project that has been there before. With the Cosine Similitary Method, percentage of similarity will be obtained. If the similarity is high, the final project is said to be tracing.