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Journal : Conten : Computer and Network Technology

OPTIMALISASI ALGORITHMA K-MEANS MENGGUNAKAN METODE PSO PADA PENYAKIT STUNTING: stunting, optimasi k-means Ulumuddin, Ulumuddin
CONTEN : Computer and Network Technology Vol. 4 No. 1 (2024): Juni 2024
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/conten.v4i1.4900

Abstract

Stunting is a linear growth disorder in newborn babies which is caused by several factors, including LBW factors, low birth weight, mother's education, household income, and so on. So clustering is needed in this case to identify stunting with mild, severe or moderate clusters. In this study, researchers used the k-means algorithm to carry out clustering. So the results obtained were 41 heavy clusters, 109 medium clusters, while 50 light clusters. In order to find out the level of accuracy in the k-means algorithm optimized with PSO, from the results of trials conducted by researchers to optimize PSO k-means, PSO was proven to be able to increase the accuracy value of standard k-means with an accuracy value of 78.88%