Pemodelan K-Means Pada Penentuan Predikat Kelulusan Mahasiswa STMIK Palangka Raya

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Lili Rusdiana Sam'ani Sam'ani

Abstract

Data mining by applying the cluster model can use the K-Means concept as a clustering method. K -Means model application can be used to classify data such as the title of graduation students based on the amount of load studies, GPA, and graduation thesis. This research was conducted to find out the results of the use of the concept of K-Means on the determination of student graduation in order to get the results in the form of an analysis of the modeling. The problem of this research is to seek to model the concept of K-Means on the determination of graduation Students using Student Data of STMIK Palangkaraya. K-Means algorithm is used through three stages: initialization , the first iteration and the second iteration. The results of the modeling is the use of K-Means algorithm to determine student graduation to obtain analysis of the results in the form of 70 % could determine the appropriate graduation of 10 data were used as a sample. Modeling using the K-Means is one of the concepts to be able to classify the data, so the use of K-Means algorithm can be a reference for the development of a modeling study, especially regarding data mining.

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How to Cite
RUSDIANA, Lili; SAM'ANI, Sam'ani. Pemodelan K-Means Pada Penentuan Predikat Kelulusan Mahasiswa STMIK Palangka Raya. Jurnal SAINTEKOM, [S.l.], v. 6, n. 1, p. 1-15, mar. 2017. ISSN 2503-3247. Available at: <http://stmikplk.ac.id/jurnal/index.php/saintekom/article/view/2>. Date accessed: 17 oct. 2019. doi: https://doi.org/10.33020/saintekom.v6i1.2.
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