文章基本信息

标题：ANALYSIS DATA OF STUDENT�S GPA AND TRAVELLING TIME TO CAMPUS USING CLUSTERING ALGORITHM AFFINITY PROPAGATION AND K-MEANS
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作者：S. JATMIKO ; R.REFIANTI ; A.B. MUTIARA 等
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2012
卷号：40
期号：2
页码：213-217
出版社：Journal of Theoretical and Applied
摘要：In most of clustering algorithm, the cluster number and member are generated randomly, called common method. Consequently, the result may vary from the same clustering process. K-means algorithm is one example of these common methods. Affinity propagation, called new method, is developed to overcome this drawback by exchange the messages between data points to test the feasibility and accuracy of all data points to become exemplar and using it to select the cluster members. The aim of this research is to compare and analyse both methods by applying these method for clustering the student grade point average (GPA) and travel time to campus data. Both algorithms are implemented using Matlab 7.11.
关键词：Affinity Propagation; Clustering; Implementation; K-Means