Penerapan Metode K-Means Untuk Cluster Calon Penerima Kartu Jombang Sehat (KJS) Berbasis Website - Syamsul Arifin, Muhammad; Arwin Dermawan, Dodik; Lazulfa, Indana (Inovate, 2022)
Clusters are very important in data grouping. Mentoro Village Government agencies have difficulty classifying population data based on poverty levels so that beneficiaries are right on target and grouping is still manual or not computerized. The purpose of this research is to create a website-based cluster system capable of grouping population data based on poverty levels so that the beneficiaries of the Kartu Jombang Sehat (KJS) are right on target. To classify population data based on the level of poverty, a method is needed, namely the K-Means method. This method is a partitioning clustering method that can separate data into different groups. The result of this research is a KJS recipient cluster system using the website-based K-Means method. The grouping results of 30 data consisted of 2 groups, where the group received KJS had 14 members and the group did not receive KJS as many as 16 people. Keywords: Cluster, Kartu Jombang Sehat (KJS), K-Means, System.