Open AccessPenerapan Data Mining dalam Meningkatkan Mutu Pembelajaran Menggunakan Metode K-MEANS Clustering
Author(s) -
Koko Handoko
Publication year - 2016
Publication title -
jurnal nasional teknologi dan sistem informasi (teknosi) universitas andalas
Language(s) - English
Resource type - Journals
eISSN - 2476-8812
pISSN - 2460-3465
DOI - 10.25077/teknosi.v2i3.2016.31-40
Subject(s) - cluster analysis , attendance , computer science , k means clustering , quality (philosophy) , cluster (spacecraft) , mathematics education , data mining , mathematics , artificial intelligence , physics , quantum mechanics , economics , programming language , economic growth
— 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.