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

  • Handoko K
N/ACitations
Citations of this article
86Readers
Mendeley users who have this article in their library.

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.

Cite

CITATION STYLE

APA

Handoko, K. (2016). Penerapan Data Mining dalam Meningkatkan Mutu Pembelajaran Menggunakan Metode K-MEANS Clustering. Jurnal Nasional Teknologi Dan Sistem Informasi, 2(3), 31–40. https://doi.org/10.25077/teknosi.v2i3.2016.31-40

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free