Open AccessImplementation of Data Mining Algorithm for Clustering of Palm Oil Harvested Data
Author(s) -
Widya Juli Mawaddah,
Indra Gunawan,
Ika Purnama Sari
Publication year - 2022
Publication title -
journal of machine learning and artificial intelligence
Language(s) - English
Resource type - Journals
eISSN - 2828-9102
pISSN - 2828-9099
DOI - 10.55123/jomlai.v1i1.163
Subject(s) - palm oil , cluster analysis , palm , data mining , value (mathematics) , process (computing) , agricultural engineering , k means clustering , algorithm , computer science , mathematics , agricultural science , engineering , environmental science , artificial intelligence , statistics , physics , quantum mechanics , operating system
Palm oil is one of the plantation commodities that has a strategic role in Indonesia's economic development. In this study, we will discuss oil palm yields at PPKS Marihat, one of the Oil Palm Research Center branches located in Simalungun Regency, Medan, North Sumatra. Know how it grows. The Clustering algorithm is used in K-Means. Using this method, the data will be grouped into 3 (three) Clusters, where the application of the K-Means Clustering process uses the Rapid Miner tools. The data used is data on oil palm harvests at PPKS Marihat in 2020, consisting of 100 data items. The results obtained are crop yields with an excellent value of 66 items, harvest data with a good deal of 32 items, and harvest data with a reasonably good value of 2 items, based on net total and gross amount for each region. Based on this, it can be concluded that the K-Means Algorithm can be used to Cluster oil palm yields at PPKS Marihat