Penerapan Algoritma K-Medoids Clustering Dalam Pengelompokkan Data Hutan Tanaman Industri Di Sumut

Abstract

One of the important points in utilizing industrial planted forests is meeting the need for industrial raw materials in the form of timber forest products and increasing productivity as a production forest. The demands of meeting the demand for raw materials for forest products for industrial use cannot be used just by any party. This is because a business permit for the utilization of timber forest products in Industrial Plantation Forests is required for HTI development that has been degraded or has decreased productivity, especially since the establishment of concessions and expansion of HTIs that are not in accordance with procedures. The government is of course increasingly demanding to be active in managing the requirements for the formation, exploitation, and expansion of HTI including the flow, procedure, and timing. So the authors conducted this study aimed at analyzing Industrial Planted Forests in the context of grouping the number of HTI expansions that had been realized from the previous plan. For this reason, it is necessary to apply the K-Medoids method. The K-Medoids method is able to measure the level grouping of industrial plantation forest expansion. The variable used is the area of industrial forest that has been realized for 3 years. So the results obtained are the number of regional industrial planting forests in North Sumatra which are the most productive in terms of expansion.