JOMLAI: Journal of Machine Learning and Artificial Intelligence
Vol. 1 No. 1 (2022): March

Utilization of K-Medoids Algorithm for Klustering of Oil Palm Sprouts

Sri Nuraini (STIKOM Tunas Bangsa, Pematangsiantar, Indonesia)
Indra Gunawan (STIKOM Tunas Bangsa, Pematangsiantar, Indonesia)
Widodo Saputra (STIKOM Tunas Bangsa, Pematangsiantar, Indonesia)



Article Info

Publish Date
18 Mar 2022

Abstract

Palm oil is still a prima donna commodity in the plantation sector and as a major foreign exchange earner to date. Research and development of this commodity is very important to maintain Indonesia's position as the largest palm oil producing country in the world. The purpose of this study was to analyze what internal and external factors are the strengths, weaknesses, opportunities and threats for marketing oil palm sprouts in PPKS Marihat. To analyze what are the priority strategies to be implemented for the marketing of sprouts at PPKS Marihat. The research method used is the K-Medoids clustering algorithm by selecting the sprout data in order to determine the best quality of sprouts. Based on the results of research using the K-Medoids algorithm with manual calculations and testing, the same results were obtained, namely cluster 1 with very good sprouts category had 7 members, cluster 2 with good sprouts category had 12 members and cluster 3 with poor sprouts category had 7 members. . Testing data on Rapid Miner using the K-Medoids algorithm can display 3 classes with an accuracy percentage of 100%. So it can be concluded that the K-Medoids algorithm can be used for clustering oil palm sprouts at PPKS Marihat.

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Journal Info

Abbrev

jomlai

Publisher

Subject

Computer Science & IT Engineering

Description

Focus and Scope JOMLAI: Journal of Machine Learning and Artificial Intelligence is a scientific journal related to machine learning and artificial intelligence that contains scientific writings on pure research and applied research in the field of machine learning and artificial intelligence as well ...