Data Mining Pengelompokan Pembayaran Listrik Menggunakan Metode Clustering - Adelia Ramadani; Achmad Fauzi; Anton Sihombing (El-Mujtama: Jurnal Pengabdian Masyarakat, 2022)
Electricity is a basic need that greatly influences all community and government activities. Almost all people from the upper to the lower classes, both in the fields of education, government, economics and social, really need a source of electrical energy as a means of supporting activities and productivity. PLN (Persero) is a State-Owned Enterprise (BUMN) that provides services to the community in the provision of electricity. The K-Means algorithm is one of the clustering technique algorithms that starts with random selection, which is the number of clusters that you want to form from the data to be clustered, namely electricity payments. the system made from k-means displays the results of the clustering of electricity payments, namely the pattern of electricity payments whose clusters are up, fixed and down. By utilizing a number of data owned by the agency, it can be grouped using data mining technology. The use of data mining techniques in classifying electricity payments is expected to be useful to simplify the process of searching for system data, which previously was still manual Keywords: Data Mining, K-Means, Electricity