Penerapan Algoritma K-Medoids Dalam Menentukan Cluster Kabupaten/Kota Berdasarkan Migrasi Penduduk Jawa Barat - Bahrul Ulum; Edi Tohidi; Nisa Dienwati Nuris (Pusat Riset dan Inovasi Nasional, 2024)
One of the three main factors influencing population dynamics is migration, along with births and deaths. Changes in population structure will definitely be influenced by migration. If in-migration is more than out-migration, the population will increase, but if out-migration is less than in-migration, the population will decrease. Therefore, it is necessary to know the grouping of regions based on population migration levels. To carry out this grouping, it is necessary to use Data mining methods. In this research, the Data mining used is Clustering using the K-Medoids algorithm. This method divides each district into predetermined groups. The K-Medoids method was chosen because it uses physical data that is not abstract and clear, which is suitable for the problem of grouping population migration data. By grouping migration levels based on districts/cities in West Java, it will be known which districts/cities in West Java have high levels of incoming migration, medium migration and high outmigration. Then recommendations can be given to the local government according to the migration level category.