PENENTUAN JUMLAH PENYEBARAN TRANSMIGRAN DENGAN METODR K-MEANS CLUSTERING (STUDI KASUS KABUPATEN TOJO UNA-UNA)

The population in Indonesia is growing at this time which causes population density in an area. The factors that influence the uneven distribution of the population are physiological, biological and cultural factors. One of the impacts of population density in an area causes job opportunities in the area to be smaller, so that the unemployment rate also increases. Tojo Una-Una Regency is one of the areas in Central Sulawesi province which still has a lot of vacant land so that the Tojo Una-Una Regency government accepts incoming transmigration. To help the government of Tojo Una-Una Regency, a system for Determining the Number of Transmigrants Spread Using the K-Means Clustering Method is needed (Case Study of Tojo Una-Una Regency). K-Means Clustering is a data analysis method that performs an unsupervised learning modeling process and uses methods to group data into various partitions. The results of this study indicate that there are three cluster groups, namely the first cluster character is low transmigration area, the second cluster character is medium transmigration area, and the third cluster character is a high transmigration area.