Penerapan Algoritma K-Means Untuk Pengelompokkan Penyakit Kronis pada Warga Lansia (Studi Kasus Pada: Posyandu Lansia RW 07)

 (*)Wargijono Utomo Mail (Universitas Krisnadwipayana, Jakarta, Indonesia)

(*) Corresponding Author

Submitted: August 29, 2020; Published: October 20, 2020

DOI: http://dx.doi.org/10.30865/mib.v4i4.2410

Abstract

Health is very valuable for all humans, anyone can experience health problems, especially for the elderly. Posyandu elderly RW 07 Pulogebang sub-district is one of the health services available for elderly residents. One of the government's efforts to deal with health problems is by establishing posyandu for elderly residents, considering how elderly people are vulnerable to health problems. At this time, health problems have the potential to attack people who are elderly, and have a history of chronic disease and a weak immune system, more likely to develop disease. In order to provide proper treatment, the elderly posyandu officers classify elderly people who have a history of chronic disease so that they can provide appropriate education and treatment. The data collection and counseling methods carried out by the elderly posyandu are still random and take turns with elderly residents in RW 07, Pulogebang sub-district. However, this method has the risk of being less accurate with the resulting data, because each resident has a different history of disease. Therefore we need an analysis of the health data of the elderly, so that it can be seen the distribution of people who have a history of chronic disease. One solution is to use data mining. So that in this study the clustering technique was used using the K-Means algorithm to classify patients with chronic disease in the elderly residents of RW 07, Pulogebang Village.

Keywords


Posyandu, Elderly Residents, Chronic Disease, K-Means Algorithm

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