Penerapan Algoritma K-Medoids Untuk Clustering Prioritas Penerima Beasiswa
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Agus Iskandar
*
Universitas Nasional, Jakarta,
Indonesia
(*) Corresponding Author
Abstract
Scholarships are a form of appreciation given to students. In college scholarships that are usually given are scholarships from foundations. The limited number of foundation scholarships provided by tertiary institutions is certainly a separate problem for elements of leadership or management. The problems encountered must be resolved as well as possible. Therefore, it is necessary to group students who are prioritized to get foundation scholarships. The process of determining priority levels for students receiving foundation scholarships has become a new problem for the management team. The process of solving the problem can be done by processing the data. Data mining is a data processing process for extracting information stored in datasets. In data mining, the process of grouping data for the priority determination process is included in the clustering technique. K-Medoids is part of clustering data mining. K-Medoids is used in data mining for the grouping process in forming clustering. The K-Medoids algorithm can help simplify the process of forming priority clusters. In this case there are 5 alternatives included in Cluster 1 and 5 alternatives included in Cluster 2. With the formation of clusters from the K-Medoids algorithm process it can be easily in the decision making process.
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