KLASTERISASI ANGKATAN KERJA DI INDONESIA BERDASARKAN USIA MENGGUNAKAN METODE ALGORITMA K-MEANS

Abstract

The concept of the population is divided into two groups, namely the working age population and the population not working age. Indonesia, which has 34 provinces, has an unequal distribution of labor force due to the level of economic growth that is still not evenly distributed in several sectors. Labor is the most important and influential element in managing and controlling the economic system. In this study the method used in the grouping of provinces was based on the workforce in 34 provinces using the K-Means algorithm. The purpose of grouping data is done to get a province grouping that has a workforce in Indonesia by grouping / clustering into 3 groups based on age groups using the K-Means algorithm. Based on the calculations, the results of cluster 0 were 6 provinces, cluster 1 as many as 3 provinces and cluster 2 were 25 provinces. The K-Means algorithm can be used to understand the workforce problems and make it easier to describe the characteristics or characteristics of each group. Based on these results, the local government can give more attention to the regions with the smallest workforce such as the Province of Central Sulawesi, East Kalimantan, Jambi so that economic growth in various sectors can be increased so that the welfare of the workforce, especially in terms of work in the field of work can be easily obtained.