Performance Comparison of Clustering Kmeans and Fuzzy Logic Tsukamoto Method among Student Prospective Scholarship Receiversat Politeknik Pos Indonesia

Main Article Content

Diki Wahyu Nugraha, Nisa Hanum Harani, Rd. Nuraini Siti Fatonah, Mahir Pradana


Student, Alumni, and Cooperation Services are institutions under the Deputy Director III. This agency has a duty to provide academic services to students on the POS INDONESIA POLITEKNIK campus, and is responsible for providing information on campus activities and academic issues to students of POLITEKNIK POS INDONESIA. Currently, the field of Student Affairs, Alumni and Cooperation, POLITEKNIK POS INDONESIA does not yet have an application for a decision support system for scholarship selection using the Tsukamoto fuzzy logic method because it still uses manual methods to determine prospective scholarship recipients. A research and application development was carried out in order to improve the quality and support the activities of the Student Affairs, Alumni and POS INDONESIA POLITEKNIK Cooperation. The method currently used in this research is the Tsukamoto Fuzzy Logic method, which is a calculation method to determine the highest criterion value based on rules, the method before the development of this decision support system uses the K-Means Clustering method where this method determines cluster 1 and Cluster 2 and has tested the calculation results. The results of this study are that it can help the process of calculating student data for prospective scholarship recipients that can be used by Student Affairs staff through the system. With this application, it can help companies in lightening the work because they do not need to use the calculation process to determine prospective scholarship recipients manually. This research is expected to be useful for companies in order to assist companies in improving student academic services and in order to be more efficient.

Article Details