ENDANG SUGIHARTI, ILKOM UNNES and MUCH. AZIZ MUSLIM, ILKOM UNNES (2016) ON-LINE CLUSTERING OF LECTURERS PERFORMANCE OF COMPUTER SCIENCE DEPARTMENT OF SEMARANG STATE UNIVERSITY USING K-MEANSALGORITHM. Journal of Theoretical and Applied Information Technology, 83 (1). pp. 64-71. ISSN 1992-8645

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Abstract

Lecturer is one of the essential components of an educational system in universities. Quality of lecturer performance can be reflected in the productivity and quality of the implementation of the Three Responsibilities that include activities in education, research, community services, and other supporting activities. Clustering of lecturer performance is required in order to gain a knowledge (knowledge discovery) of the pattern of the Three Responsibilities implementation, in this case in the Department of Computer Science Unnes. Clustering is also necessary to control the balance of lecturer performance in implementing the Three Responsibilities. This is why the research was conducted.The problem is how to create an inovative program in the form of Clustering On-line of Computer Science Department for lecturer performance based on the implementation of the Three Responsibilities using of K-Means Algorithm? The objective of this institution research in order to obtain on-line information system for clustering of Computer Science Department for lecturer performance using the K-Means Algorithm. To resolve this problem, researchers divided into two stages of completion. The first stage was literature review. The second stage was making a clustering program for Lecturer performance of Department of Computer Science, based-on the implementation of College three responsibilities. The works sequence were: (1) Data Collection, (2) Building a data mining system, (3) Data Processing, (4) Conducting the clustering process with K-Means algorithm. Analysis of data/results included: (1) data reduction; (2) data display; and (3) conclusion (verification). As the results of this research, now the Department of Computer Science Unnes already has a clustering program that is capable of classifying and monitors all activities of lecturers performance in accordance with the implementation of College three responsibilities.

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