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DOI: 10.14569/IJACSA.2025.0161299
PDF

Spatial Classification of Fertilizer Requirements Using Fuzzy C-Means on Shallot Agricultural Land

Author 1: Roghib Muhammad Hujja
Author 2: Ahmad Ashari
Author 3: Danang Lelono
Author 4: Agus Prasekti

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 16 Issue 12, 2025.

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Abstract: Spatial variability in soil fertility constrains productivity in intensive shallot farming, yet fertilizer is frequently applied uniformly across fields. This practice results in nutrient inefficiencies, increased costs, and heightened environmental risks. This study introduces a fertilizer requirement mapping framework utilizing Fuzzy C-Means (FCM) clustering, a machine learning technique for data grouping, applied to in-situ measurements of soil Nitrogen (N), Phosphorus (P), and Potassium (K). The framework was evaluated in a 500 × 500 m shallot field in Srikayangan, Kulon Progo, Indonesia, subdivided into 10 × 10 m management blocks suitable for smallholder operations. Soil NPK levels were measured using IoT sensor nodes and georeferenced with GNSS, while high-resolution RGB imagery from a UAV provided spatial context. Normalized NPK data were clustered with FCM to delineate fertility zones exhibiting nutrient differences. To operationalize clustering results, a nutrient-priority decision logic identified the most limiting nutrient (N, P, or K) for each block. Fertilizer recommendation points were visualized on a UAV-derived orthomosaic map to facilitate interpretation and field application. The results indicate that this approach effectively captures gradual fertility transitions and produces actionable fertilizer zones for site-specific nutrient management (SSNM) in smallholder systems. The study demonstrates the practical integration of fuzzy clustering, IoT-based soil sensing, and UAV mapping to inform precision agriculture decisions.

Keywords: Fuzzy C-Means (FCM); soil fertility zoning; NPK (Nitrogen, Phosphorus, Potassium); fertilizer recommendation; precision agriculture; Site-Specific Nutrient Management (SSNM); IoT (Internet of Things); UAV (Unmanned Aerial Vehicle)

Roghib Muhammad Hujja, Ahmad Ashari, Danang Lelono and Agus Prasekti. “Spatial Classification of Fertilizer Requirements Using Fuzzy C-Means on Shallot Agricultural Land”. International Journal of Advanced Computer Science and Applications (IJACSA) 16.12 (2025). http://dx.doi.org/10.14569/IJACSA.2025.0161299

@article{Hujja2025,
title = {Spatial Classification of Fertilizer Requirements Using Fuzzy C-Means on Shallot Agricultural Land},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0161299},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0161299},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {12},
author = {Roghib Muhammad Hujja and Ahmad Ashari and Danang Lelono and Agus Prasekti}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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