PENERAPAN ALGORITMA K-MEANS DALAM KLASIFIKASI JUMLAH PENDUDUK JAKARTA SELATAN - Tamba, Reynold Julian; Suharso, Aries; Purwantoro, Purwantoro (LPPM Institut Teknologi Bisnis Dan Bahasa Dian Cipta Cendikia, 2024)
This research is a case study conducted at the Directorate General of Population and Civil Registration with the aim of grouping the population based on sub-district and gender, and the method used is the K-Means algorithm. The evaluation results using the silhouette coefficient method show that K-Means is the best algorithm because it obtained a value of 0.7774399276167493. In this study, there were 39 types of population density analyzed, of which 6 were classified as low (cluster 0), 20 were in the middle group (cluster 1), and 8 were middle group (cluster 2), and 6 were the highest (cluster 3). This research makes an important contribution in determining the amount of increase or decrease in population density each year.