<![CDATA[In the National Leading Plantation Statistics yearbook issued by the Directorate General of Plantation, Ministry of Agriculture of the Republic of Indonesia, it is stated that Indonesia is the world's number one producer of palm oil and also the owner of the largest oil palm plantation area in the world. Indonesia's palm oil production reached 43.5 million tons, with an average growth percentage of 3.61%. The Coordinating Minister for Economic Affairs considered that the palm oil sector had a major role in the economy during the Covid-19 pandemic. The palm oil sector is able to maintain 16.2 million workers who depend on it in the midst of the pandemic. Therefore, it is necessary to map oil palm plantations from each province of Indonesia so that it can be seen which areas have the potential to produce oil palm. Thus, later the area can be maximized again productivity. Then, to find out also which provinces have a low potential level of palm oil production so that later the productivity of the area can be assisted by analyzing what patterns can be found from the highest potential level of oil palm production. In this research, mapping will be carried out using clustering techniques in data mining, using the k-medoids algorithm. The results showed that there were 3 clusters, namely cluster 1 (category of provinces with low production areas of oil palm), cluster 2 (category of provinces with high production areas of oil palm), and cluster 3 (category of provinces with medium production areas of oil palm). ). The silhouette coefficient evaluation result in the model calculation using this technique is 0.64. This range value is included in the medium structure criteria (good cluster structure).]]>
Copyrights © 2022
