Optimizing K-Means Algorithm Using the Purity Method for Clustering Oil Palm Producing Regions in North Aceh

Optimizing K-Means Algorithm Using the Purity Method for Clustering Oil Palm Producing Regions in North Aceh

The K-Means algorithm is a fundamental tool in machine learning, widely utilized for data clustering tasks. This research aims to improve the performance of the K-Means algorithm by integrating the Purity method, specifically focusing on clustering regions renowned for oil palm production in North...

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Bibliographic Details
Main Authors: Novia Hasdyna, Rozzi Kesuma Dinata, Balqis Yafis
Format: Article
Language:English
Published: Universitas Islam Negeri Sunan Kalijaga Yogyakarta 2025-01-01
Series:JISKA (Jurnal Informatika Sunan Kalijaga)
Subjects:
K-Means Algorithm, Purity Method, Data Clustering, Oil Palm Production, North Aceh, Davies-Bouldin Index (DBI)
Online Access:https://ejournal.uin-suka.ac.id/saintek/JISKA/article/view/4817
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https://ejournal.uin-suka.ac.id/saintek/JISKA/article/view/4817

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