Geographic Information System Mapping and Management of Child with the Highest Nutritional Potential in Prabumulih City Using K-Means Clustering Method
(Case Study: Prabumulih City Health Office)
- DOI
- 10.2991/ahe.k.220205.065How to use a DOI?
- Keywords
- Malnutrition; Clustering; k-means; eXtreme Programming
- Abstract
Malnutrition is one of the diseases that Indonesia is worried about, not only a burden on the state, but also a burden on the family. Of course this is also a concern of the local government, including Prabumulih City. Based on a report from the family health and community nutrition section at the Prabumulih City Health Office, in 2019 the number of cases of malnutrition in children under five reached 1%. And to maximize health monitoring in toddlers so that they are not potentially bad, clustering is carried out using the K-Means algorithm which aims to provide information for the parties involved in decision making. The system development method used is eXtreme Programming (XP). The data used is a recap of data on toddlers with bad potential from 2018 - 2020. This study resulted in clusters (groups) of bad disaster distribution areas with a level of C1 for areas with high nutritional potential, C2 for areas with moderate nutrition levels. potential, for C3 for areas of low potential malnutrition.
- Copyright
- © 2022 The Authors. Published by Atlantis Press International B.V.
- Open Access
- This is an open access article under the CC BY-NC license.
Cite this article
TY - CONF AU - Leni Novianti AU - Robinson Robinson AU - Ienda Meiriska AU - Resti Atika Sari PY - 2022 DA - 2022/02/14 TI - Geographic Information System Mapping and Management of Child with the Highest Nutritional Potential in Prabumulih City Using K-Means Clustering Method BT - Proceedings of the 5th FIRST T1 T2 2021 International Conference (FIRST-T1-T2 2021) PB - Atlantis Press SP - 369 EP - 374 SN - 2589-4943 UR - https://doi.org/10.2991/ahe.k.220205.065 DO - 10.2991/ahe.k.220205.065 ID - Novianti2022 ER -