Open AccessPenerapan K-Means Clustering Untuk Pengelompokan Kelas Pada Taman Kanak-Kanak
Author(s) -
Dewi Anggraeni,
Rizaldi Rizaldi,
Guntur Maha Putra
Publication year - 2021
Publication title -
building of informatics, technology and science
Language(s) - English
Resource type - Journals
eISSN - 2685-3310
pISSN - 2684-8910
DOI - 10.47065/bits.v3i3.1125
Subject(s) - cluster analysis , class (philosophy) , division (mathematics) , matching (statistics) , object (grammar) , mathematics education , cluster (spacecraft) , computer science , variable (mathematics) , psychology , research object , artificial intelligence , mathematics , statistics , arithmetic , geography , mathematical analysis , regional science , programming language
Basically, children aged 5 years can recognize letters, match shapes, recognize class colors and easily adapt to the environment. However, there are some children who only have the ability to read, but do not have other abilities, as well as other children. Based on the observations, the researchers conducted research on the application of k means clustering to classify classes in kindergarten. The object of this research is students who study in TK ABA XI. The method used for division is the k means clustering method, where this method can group data in small amounts or in large amounts of data. There are 2 variables, namely the variable class_safa_and_Kelas_marwa. Where each variable has criteria, namely A = Activeness, B = Matching Pictures, C Knowing Color, D = Knowing Shapes, E = Writing. The result of this research is the calculation of k means cluster in grouping classes in kindergarten students can be a reference for teachers in terms of class division. The student grouping data is according to the desired class capacity and the number of classes can change according to the school's wishes.