Penerapan Metode K-Means dalam Klasterisasi Status Desa terhadap Keluarga Beresiko Stunting - Dayla May Cytry; Defit, Sarjon; Nurcahyo, Gunadi (Universitas Putra Indonesia YPTK Padang, 2023)
The Indonesian government issued Presidential Regulation of the Republic of Indonesia Number 72 of 2021 concerning the acceleration of stunting reduction with a prevalence target of 14% by 2024. Stunting has now become a national issue and is of particular concern to the government to overcome the risks it poses. One action that can be taken to prevent stunting is to provide intervention to families at risk of stunting. This intervention is carried out in the form of clustering of sub-districts or villages consisting of babies under two years (baduta), babies under five years (toddlers), and pregnant women with inadequate environmental aspects (sanitation and clean water). Based on this, this research aims to conduct a cluster analysis of sub-districts or villages that are at risk of stunting. The cluster analysis method uses the K-Mean algorithm with reference to 3 clusters, namely low, medium, and high. This research uses a dataset of 71 sub-districts or villages that are at risk of stunting. The research results show that the performance of the K-Means method in cluster analysis produces 32 low-risk sub-districts or villages, with a percentage of 45.07%, 36 medium risks with a percentage of 50.70%, and 3 high risk with a percentage of 4. 23%. Based on these results, this research can contribute to the relevant government in dealing with the spread of stunting