K-Medoids: Inflation Clustering of 90 Cities in Indonesia (January-October 2020)

Abstract

Inflation affects society and the economy of a country. For the general public, inflation is a concern because inflation directly affects the welfare of life, and for the business world, the inflation rate is a very important factor in making various decisions. Therefore, the aim of this study is to cluster the inflation rate that occurs in 90 cities in Indonesia, so that it is known which cities have high, medium, or low inflation levels. The grouping algorithm used is K-Medoids data mining. The research data is quantitative data, namely inflation data that occurred in 90 major cities in Indonesia from January to October 2020. The data was obtained from the Indonesian Central Statistics Agency. The clustering in this study is divided into 5, among others: cities with very high inflation rates, cities with high inflation rates, cities with moderate inflation rates, cities with low inflation rates, and cities with very low inflation rates. Based on the results of clustering analysis using rapidminer, for cities with a very high inflation rate category consists of 1 city (available on Cluster_4), high category consists of 4 cities (Cluster_0), medium category consists of 4 cities (Cluster_3), low category consists of 79 cities (Cluster_2) and very low category consisted of 2 cities (Cluster 1). This can provide information for the Indonesian government to keep the inflation rate stable.