Pengelompokan Data Pengangguran Terbuka Menggunakan Algoritma K-Means Berdasarkan Provinsi Jawa Barat

Abstract

Unemployment is a problem that always arises every year. Open unemployment is categorized as a workforce that is still trying to find work and prepare for business. The long-term impact of unemployment is psychologically bad for the unemployed and their families. Unemployment is a problem that has a very bad impact on the economy and society, therefore it is necessary to make continuous efforts to overcome it. In this study the data used comes from West Java Open Data for 2013-2021. This study uses a data mining technique, namely the K-Means Algorithm. The K-Means method is a clustering method used to divide a data set into several groups. The purpose of this study was to obtain the results of the grouping of districts/cities in West Java Province based on the unemployment rate sinto 2 parts, namely the group with the high unemployment rate and the group with the low unemployment rate. From the grouping results obtained 110 the low cluster and 104 the high cluster. The results of this study are one way the government can create and expand employment opportunities to improve the economy. Especially districts/cities that have minimal employment which causes unemployment. It is hoped that this research can provide information and input for the government so that it can pay more attention to districts/cities in West Java that are included in the category of hih unemployment.

Keywords— Data Mining, K-means Algorithm, Unemployment, Clustering.