Application Of Data Mining Classification Of Student Ability In Learning Using The K-Means Clustering Algorithm Method (Case Study : Sd Negeri 056029 Karya Utama)

Ika Indah Rahayu; Yani Maulita; Husnul Khair

doi:10.55227/ijhet.v1i3.47

Authors

Ika Indah Rahayu STMIK Kaputama Binjai, Sumatera Utara
Yani Maulita STMIK Kaputama Binjai Sumatera Utara
Husnul Khair STMIK Kaputama Binjai Sumatera Utara

DOI:

https://doi.org/10.55227/ijhet.v1i3.47

Keywords:

Data Mining, Clustering, Student Achievement

Abstract

The high level of student success and the low level of student failure is a quality of the education world. The world of education is currently required to have the ability to compete by utilizing all resources owned. In addition to facilities, infrastructure and human resources, information systems are one of the resources that can be used to improve competency skills. Data mining is a process of data analysis to find a dataset of data sets. Data mining is able to analyze large amounts of data into information that has meaning for decision supporters. One process of data mining is clustering. Attributes used in the grouping of student achievement are Name, Extracurricular, Value which include UAS Value, . The case study of 20 students with distance calculation using manhattan distance, chbychep distance and euclidian distance yielded 67% accuracy. Keywords: data mining, clustering, k-means, student achievement

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