KLUSTER K-MEANS DATA MAHASISWA BARU TERHADAP PROGRAM STUDI YANG DIPILIH

Citra , Arum Sari and Dwi , Sukma D (2013) KLUSTER K-MEANS DATA MAHASISWA BARU TERHADAP PROGRAM STUDI YANG DIPILIH. Tekmapro : Journal of Industrial Engineering and Management, 8 (2). 136 p.-143 p.. ISSN 1907-5146

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Abstract

The amount of interest from each subject at UPNV East Java is different. Based on this, the research aims to group study program to provide information to the University so as to prioritize the program of study with little interest. The data used is the data the student population in 2013/2014 UPNV East Java from each subject. The independent variable in this study is the origin of high school, parental income and home town. Data obtained from the Bureau Admik UPNV East Java, using data mining techniques, while processing the data using K-Means clustering to group courses in several classes based on the similarity of data. Based on the results of the clustering method K-Means algorithm, it can be concluded that there are three clusters, where cluster 1 is a program of study with little interest in as many as 10 courses, cluster 2 is many enthusiasts as many as 5 courses and clusters 3 is quite interested by 4 courses.

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