Penerapan Metode K-Means untuk Clustering Data Anak Berdasarkan Kepemilikan Akta Kelahiran dan KIA - Diah Ayu Rahmayanti (Faculty of Computer Science, University of Jember, 2022)
Having a birth certificate and KIA is very important for every child to have as proof of identity. However, in reality, the number of birth certificates and KIA in Manokwari Regency is not proportional to the number of children. This study aims to classify children's data based on the number of birth certificates and ownership of KIA in Manokwari district by using the K-Means clustering method to produce sub-district groupings with high coverage of non-ownership of birth certificates and KIA, so that it can assist the Department of Population and Civil Registry of Manokwari Regency in provide targeted service programs. This study uses the Davies Bouildin Index (DBI) method to determine the optimum number of clusters used. The optimum number of clusters obtained is 4 with the lowest DBI value of 0.069 so that 4 clusters are formed, namely cluster 0 with a fairly low coverage category, cluster 1 with a fairly high coverage category, cluster 2 in a high coverage category, and cluster 3 in a very high coverage category. The K-Means clustering method succeeded in grouping sub-districts in Manokwari district, as well as informing the number of sub-districts with high coverage that do not have birth certificates and KIA.