Penerapan Data Mining dalam Meningkatkan Mutu Pembelajaran Menggunakan Metode K-MEANS Clustering

Authors

  • Koko Handoko LPPM Universitas Putera Batam

DOI:

https://doi.org/10.25077/TEKNOSI.v2i3.2016.31-40

Keywords:

Data to Improve Learning, Data Mining, K-Means Clustreing, RapidMiner

Abstract

Abstract— This research applies data mining using clustering methods to improve the quality of learning in Higher Education Institutions in the Program TKJ Community College South Solok. The algorithm used is K-Means Clustering is a process of grouping a number of data or object into a cluster (group) so that each cluster will contain the data that is as similar as possible and different from the objects in other clusters. Testing is done with RapidMiner 5.3 applications that generate clusters in improving the quality of learning. The samples used were taken from the data tables of students who have ditrasformasi. Where the variables are defined as the first test four variables, namely: IP students, distance students, attendance and parental income. Where the students will present data with the quality of teaching is very good, good, good enough, and less good.

Author Biography

Koko Handoko, LPPM Universitas Putera Batam

Teknik Informatika

References

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Submitted

2016-08-18

Accepted

2016-11-12

Published

2016-12-14

How to Cite

[1]
K. Handoko, “Penerapan Data Mining dalam Meningkatkan Mutu Pembelajaran Menggunakan Metode K-MEANS Clustering”, TEKNOSI, vol. 2, no. 3, pp. 31–40, Dec. 2016.

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