Application of decision support system using the K-Nearest Neighbor and Weighted Product method for determining the recipients of low-income family scholarship (GAKIN) (case study: Poltekkes Kemenkes Semarang)

Abstract

Poltekkes Kemenkes Semarang is a university of health that has a scholarship facility for underprivileged students or often referred as Beasiswa Keluarga Miskin (Gakin). At this time the determination of Gakin scholarship recipients is still in the form of manual selection.Decision-Making is a systematic approach to a problem with the gathering of facts, a mature determination of the alternatives to be faced, and the taking of actions that are calculated to be the most appropriate action. To simplify the process of determining a decision, present an application of decision support system with input and output required. This research makes an application of decision support system with K-Nearest Neighbor method to recommend the decision in the system. It aims to shorten the time and provide convenience to policymakers (decision makers) in Poltekkes Kemenkes Semarang in selecting recipients of Poor Family Scholarships (GAKIN). Based on existing data, KNN method can handle all new data from potential recipients with a value of neighbor is 5 to produce an accuracy of 99.61%, precision 99.85% and recall 99.42% with data of scholarship recipients last five years.