The Mapping Model is in the form of Clustering of Workers' Hourly Wages by Region in Indonesia using the K-Means Method - S Suhendra; Siti Aisyah (IJISTECH (International Journal of Information System and Technology), 2020)
Wages are a very important element in manpower activities because the main purpose of working people is to get wages or salaries which will be used to meet daily needs. The hourly wage system for workers in the Province affects the wages received by workers. The research objective is to create a cluster model of the hourly wages of workers in Indonesia by region. The data used in the mapping is data on workers' hourly wages for 2017-2018, which are managed by the Central Statistics Agency (abbreviated as BPS). The technique used is clustering with the k-means method, which is part of data mining. This process uses two cluster labels, namely the high wage cluster (C1) and the low wage cluster (C2), with a maximum Davies Bouldin value of 0.490. The research results were obtained from 34 regions in Indonesia, twenty-seven provinces were in the low category cluster (C2), and seven provinces were in the high category (C1). This can be used as input for the provincial government to make policies on hourly wages in Indonesia that have an impact on the welfare of the community.