Aldi Nurzahputra, ILKOM UNNES and Much Aziz Muslim, ILKOM UNNES and Roni Kurniawan, ILKOM UNNES (2016) Online Fuzzy C-Means Clustering for Lecturer Performance Assessment Based on National and International Journal Publication. In: International Conference on Mathematics, Science, and Education (ICMSE 2016.

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Abstract

One way that can be done to determine the quality of lecturer performance is to conduct an assessment of the number of scientific publications have been conducted by the lecturers. The data of Mathematic and Natural Science Lecturer Lecturer, Unnes, totaled 160 lecturers will be assessed based on national and international journal publications. By using these data sources, will be applied data mining using Fuzzy C-Means algorithms and clustering method. Clustering method is one of the main methods of data analysis to help identify a grouping of data objects (cluster) of the dataset. The data of lecturer journal publications will be processed by a variable that is used as the assessment benchmark are index Scopus, journal accreditation, and the index DOAJ. So it will be found knowledge, information, and performance assessment of lecturers into four clusters which consisting of various lecturers. From the results of clustering using C-Means Clustering then obtained the FMIPA lecturer performance assessment on national and international journal publication.

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