Implementation of K-Means Algorithm for Diseases Clustering in Elderly Posyandu Participants

Firdaus, Muhammad Iqbal (2022) Implementation of K-Means Algorithm for Diseases Clustering in Elderly Posyandu Participants. Applied Technology and Computing Science Journal, 5 (1). pp. 11-20. ISSN 2621-4458

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Official URL: https://journal2.unusa.ac.id/index.php/ATCSJ/artic...

Abstract

The Posyandu of Tirem Village is one of the integrated service posts for the elderly, where they can get proper health services. To get the right health services, Posyandu officers group elderly posyandu participants who suffer from chronic diseases for counseling and treatment. The problem that occurred during the process of recording disease data and counseling carried out by officers was that calculations were still basic and were carried out alternately for elderly Posyandu participants in Tirem village. So this method has the risk of inaccurate data collection and inconsistent handling for the treatment of elderly residents due to different health histories among the elderly. This study aims to classify the data of elderly posyandu participants in Tirem Village who suffer from chronic diseases with predetermined attributes. This grouping process uses the Clustering method using the K-Means Algorithm. The data used in the form of 40 elderly posyandu participant data in October 2022. The results of data processing using the K-Means algorithm with Microsoft Excel tools and using RapidMiner obtained the same results, namely Cluster 1 and cluster_0 have a total of 32 data from 40 data, Cluster 2 and cluster_1 have a total of 8 data from 40 data

Item Type: Article
Uncontrolled Keywords: Chronic Diseases, Cluster, Elderly posyandu participants, K-Means Algorithm, Posyandu
Subjects: Engineering > Informatics Engineering
Engineering
Divisions: Faculty of Engineering > Informatics Engineering Study Program
Depositing User: Muhammad Iqbal Firdaus
Date Deposited: 13 Nov 2023 22:53
Last Modified: 13 Nov 2023 22:53
URI: http://eprints.umg.ac.id/id/eprint/9173

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