Cluster Analysis for Learning Style of Vocational High School Student Using K-Means and FUZZY C-MEANS (FCM)

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Published: Dec 18, 2017
DOI: https://doi.org/10.17933/jppi.v7i2.126
Keywords:
data mining, learning style, clustering, FCM, K-means
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REZA ANDREA
STMIK Widya Cipta Dharma
http://orcid.org/0000-0003-4590-7979
Shinta Palupi
STMIK Widya Cipta Dharma
Siti Qomariah
STMIK Widya Cipta Dharma

Abstract

The inability of students to absorb the various knowledge conveyed by the teacher is not due to the inability of his understanding and not because the teacher is not able to teach, but rather due to the incompatibility of learning styles (learning style) between students and teachers, so that students feel uncomfortable learning to certain teachers, it occurred also in SMKN 2 Penajam Paser Utara (PPU), research to analyze cluster (group) type of student learning by applying data mining method that is K-means and Fuzzy C-means (FCM). The goal to be achieved is to know the effectiveness of this type of learning clustering on the development of absorptive capacity and improvement of student achievement. In this research, the method used to cluster the learning type with data mining process starting from data cleaning, data selection, data transformation, data mining, pattern evolution, and knowledge (knowledge).

Article Details

Issue
Vol. 7 No. 2 (2017): Desember 2017
Section
Informatics

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