Implementasi Algoritma K-Medoids Clustering Dalam Pengelompokan Angka Kelahiran Di Kota Pematang Siantar

Abstract

Birth rate is an element of natural population growth. Birth is a term used in the demographic field to describe the number of children actually born alive. The high birth rate in Indonesia is still a major problem in population, population and environmental problems or the main problem of population in Indonesia, namely the number and population growth that is highly developed, population distribution, population age composition, and quality of population. To solve the problem that there is a method used in this study is the K-Medoids Clustering method, using 2 Clusters namely low Clusters and Clusters This study aims to determine the population density and to determine the birth of children each year based on the village. In this study using data mining techniques with the k-Medoids clustering method, the source of this data was obtained from the Office of Population and Civil Registration Pematangsiantar. Input data is data on the number of birth rates in 2015-2019 which consists of 53 villages divided into 2 clusters, namely low clusters and high clusters from the calculation of K-Medoids obtained as many as 43 villages as low clusters, 10 villages as high clusters. The implementation process using the RapidMinner 5.3 application is used to help find accurate values.