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All Journal JSTAR
Firrar Ayu Hastungkara Sudrajat
Badan Pusat Statistik
Humanities Computer Science & IT Economics, Econometrics & Finance Social Sciences

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Journal : JSTAR

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KLASTERISASI USAHA PERTANIAN PERORANGAN TANAMAN PANGAN DI PROVINSI NUSA TENGGARA TIMUR: PERBANDINGAN ALGORITMA K-MEANS DAN K-MEDOIDS Apriliani Gustiana; Firrar Ayu Hastungkara Sudrajat
Jurnal Statistika Terapan (ISSN 2807-6214) Vol 5 No 2 (2025): Jurnal Statistika Terapan
Publisher : Badan Pusat Statistik Provinsi NTT

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64930/jstar.v5i2.125

Abstract

Agricultural Development is one of main goals outlined in the Dasa Cita of Nusa Tenggara Timur’s (NTT) Governor and Vice Governor. In line with that, advancing the agriculture, plantation, livestock, fisheries and maritime sectors as leading sectors that sustainable and based on regional potential is the first foundation stated in Program 7 Pilar NTT Government. This paper examines the clustering of Individual Agricultural Holdings (UTP) using Sensus Pertanian 2023 data on five predominant variety of food crops (dry land paddy, wet land paddy, maize, cassava, sweet potato) in order to reveal heterogeneity in food crop orientation by regencies/municipality in NTT and to inform targeted, evidence-based agricultural support. The methodology used for clustering are K-Means and K-Medoids which is then evaluated with Davies–Bouldin Index (DBI) and Silhouette Coefficient. The results showed that the optimal number of clusters in this study were four clusters. K-Medoids performs best (DBI = 0.86; silhouette = 0.40), slightly outperforming K-Means (DBI = 0.88; silhouette = 0.39). The resulting clusters can be differentiated into UTP Dryland Paddy, UTP Wetland Paddy, UTP Secondary Food Crops (maize, cassava, sweet potato), and Non-Concentration, offering actionable guidance for policy making.
Co-Authors Apriliani Gustiana