Open AccessPenerapan Algoritma K-Means Dalam Pengelompokan Kepadatan Penduduk Menurut Kecamatan di Kabupaten Simalungun
Author(s) -
Devi Gultom,
Indra Gunawan,
Ika Purnamasari,
Sundari Retno Andani,
Zulia Almaida Siregar
Publication year - 2022
Publication title -
terapan informatika nusantara
Language(s) - English
Resource type - Journals
ISSN - 2722-7987
DOI - 10.47065/tin.v2i10.1375
Subject(s) - population , cluster (spacecraft) , cluster analysis , mathematics , statistics , computer science , demography , sociology , programming language
One of the problems related to population that still has to be faced by Simalungun is the problem of the imbalance in the distribution of the population. Incomplete division of the population brings problems to population density and population pressure in an area. This study uses data sources from the Central Statistics Agency (BPS) Simalungun. The data used in this study is data from 2015-2019 which consists of 32 Districts. Therefore, the researchers used the K-Means algorithm in clustering 32 sub-districts in Simalungun Regency. The data will be processed by clustering in 3 clusters, namely clusters with high population levels, clusters with moderate population levels and clusters with low population levels. The iteration process takes 5 times so that the results obtained are 4 sub-districts with high population level clusters (C1), 11 cluster sub-districts with moderate population level (C2) and 17 cluster sub-districts with low population level (C3)