ANALISIS DATA UPAH MINIMUM REGIONAL (UMR) MENGGUNAKAN METODE CLUSTERING, K-MEANS, HIERARHICAL CLUSTERER

Abstract

This study aims to analyze regional minimum wage data (UMR) in Indonesia using 3 algorithms, namely Simple K-Means, Percentage Split, and Hierarchical Clusterer by using Weka tools to see the results. The purpose of this data processing is to clarify data from Regional Minimum Wages (UMR) from several regions to determine the average income of employees. In processing this data there are several restrictions to facilitate the process. The data used is data from the Central Statistics Agency (BPS). The attributes used are Province Name, Year, UMR. 
Keywords: Weka, Regional Minimum Wage (UMR), Simple K-Means, Percentage Split, and Hierarchical Clusterer.