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All Journal Jurnal Penelitian Pendidikan IPA (JPPIPA) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JAMI: Jurnal Ahli Muda Indonesia Journal of System and Computer Engineering Jurnal Computer Science and Information Technology (CoSciTech) AJAD : Jurnal Pengabdian kepada Masyarakat Jurnal Pengabdian Inovasi dan Teknologi Kepada Masyarakat Internet of Things and Artificial Intelligence Journal Proceeding Applied Business and Engineering Conference Amare Innovative: Journal Of Social Science Research Jurnal Sains dan Ilmu Terapan Lentera: Multidisciplinary Studies Jurnal Elektronika dan Teknik Informatika Terapan Abdimas Terapan: Jurnal Pengabdian Kepada Masyarakat Terapan Journal of Innovative and Creativity Science and Technology: Jurnal Pengabdian Masyarakat Inovasi Teknologi Masyarakat Lentera: Multidisciplinary Studies
Fenty Kurnia Oktorina
Politeknik Kampar
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Journal : Jurnal Penelitian Pendidikan IPA (JPPIPA)

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Using K-Means Clustering to Analyze Socio-Economic Welfare of Oil Palm Farmers for Decision Support and Contextual Learning Integration Oktorina, Fenty Kurnia; Zulfikar; Am, Andri Nofiar; Nurkholis; Pramono, Agung
Jurnal Penelitian Pendidikan IPA Vol 11 No 4 (2025): April
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i4.10975

Abstract

This study aims to cluster the welfare levels of oil palm farmers in Gading Sari Village, Tapung, using the K-Means Clustering algorithm. The analyzed variables include land area, family dependents, average monthly income, additional income, and educational attainment. Previous studies have extensively discussed the welfare of oil palm farmers. This research uses clustering methods to uncover new and more detailed findings about the welfare of oil palm farmers in rural areas. This approach offers a fresh perspective and can be utilized to support data-driven decision-making processes by the government. Data were collected through interviews with 111 oil palm farmers, processed through normalization, and analyzed using the elbow method to identify the optimal number of clusters. The results identified three main clusters: low, medium, and high welfare levels. Land area and average monthly income were the most significant differentiating factors among the clusters. This study's fundamental distinction lies in applying the K-Means algorithm to integrate the socioeconomic aspects of oil palm farmers into specific clusters. These clusters will provide new insights into their welfare conditions. The findings are expected to assist governments and stakeholders in designing more effective and targeted development programs for oil palm
Co-Authors Agung Pramono, Agung Aldri Frinaldi Am, Andri Nofiar Andri Nofiar Anggun Dinda Putri Milenia Antoni Pribadi Antoni Pribadi Apriana Malinda Tamba Dasman Lanin Fina Nasari Fina Nasari Fitri Fitri Fitri Fitri Fitri Fitri Fitri habibie, indra Jazman, Muhammad Khairul Abidin Mahdiawan Nurkholifah Muhammad Jazman Muhammad Ridwan Muhammad Ridwan Muhammad Ridwan Nasari, Fina Niken Ellani Patitis Nofiar, Andri Nur Asma Deli Nurkholis Nurkholis Nurkholis Perdana, M. Alkadari Pribadi, Antoni Putri, Tara Liana Ramadhani Rembrandt, Rembrandt Rika Aryati Rukhshah, Muhammad Slamet Triyanto Slamet Triyanto Slamet Triyanto Zulfikar Zulfikar Zulfikar Zulfikar