Memanfaatkan Algoritma K-Means Dalam Memetakan Potensi Hasil Produksi Kelapa Sawit PTPN IV Marihat

Abstract

Based on data on the results of oil palm production in PTPN IV Marihat displays several locations with fruit yields that vary in number. For this reason, grouping of potential fruit-producing locations is needed to know which locations produce large or small numbers of palm fruit. The production sharing is usually done based on the location or block of harvesting oil palm fruit. Therefore, a method is needed to facilitate the grouping of fruit producing locations. With the K-Means clustering approach, the division of location groups can be done based on harvested area (Ha), production realization (kg) and harvest year. In this research, clustering of potential fruit-producing areas was carried out using the K-Means algorithm. By using K-Means aims to facilitate the grouping of a block with a lot of fruit production, and low. The result of this research is that C1 (highest) is 14 Harvest Block data, and C2 (lowest) is 11 Harvest Block data.

Keywords

• grouping
• data mining
• cluster
• k-means algorithm
• palm