Penerapan Algoritma K-Means Clustering untuk Pengelompokan Harga Eceran Beras di Pasar Tradisional Berdasarkan Wilayah Kota

Abstract

Rice is the main food commodity of the Indonesian people, almost all residents in this country consume rice every day. This causes rice commodities to have a very strategic value, apart from being in control of the lives of many people, it can also be used as a parameter of the country's economic and social stability. This study discusses the application of K-Means Clustering Algorithm for Grouping Retail Prices of Rice in Traditional Markets. The source of this research data is collected based on documents describing the retail price group of rice produced by the National Statistics Agency. The data used in this study are data from 2011-2016 consisting of 33 cities. Data is processed by clustering in 3 clusters, namely high population level clusters, medium and low population level clusters. Centroid data for high population level clusters 10,776, Centroid data for moderate population level clusters 9,436 and Centroid data for low population clusters 8,590. To obtain an assessment based on the grouping of the average retail price of rice in traditional markets in 33 cities with high clusters (C1) of 11 cities namely Padang, Pekanbaru, Tanjung Pinang, Bandar Lampung, Jakarta, Pontianak, Palangkaraya, Banjarmasin, Ternate, Jayapura and Manokwari for medium cluster (C2) as many as 11 cities and for low cluster (C3) as many as 11 cities. From the results of this study can be used as input for the government, especially in cities, so that cities that are included in the high cluster can normalize the retail price of rice in each city area.