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A Fuzzy Multi-Criteria Decision-Making Framework for Soil-Based Cultivation Block Selection in Citrus Orchards Adi Yusuf Arrasyid; Oka Ardiana Banaty; Adrinoviarini Adrinoviarini; Niken Ayu Widya Ningrum
Nusantara Journal of Artificial Intelligence and Information Systems Vol. 2 No. 1 (2026): June
Publisher : Faculty of Engineering and Computer Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47776/nuai.v2i1.2065

Abstract

Selecting the optimal cultivation block in a multi-plot citrus orchard is a hard multi-criteria problem when the soil criteria mix categorical and numerical measurements. Descriptors like Munsell color, soil structure, and consistency sit alongside numerical pH, and conventional agronomic assessment offers no systematic way to weigh them against each other. This study builds a decision support system (DSS) that pairs the fuzzy analytic hierarchy process (FAHP) with two ranking methods, TOPSIS and Simple Additive Weighting (SAW). A rule-based triangular fuzzy number (TFN) protocol first converts the categorical descriptors into numerical inputs through documented rules. Field data came from seven plots across five citrus variety blocks at IP2SIP Tlekung, BRMP Jestro, Batu, East Java, covering texture, structure, color, consistency, and pH. FAHP weights gave a consistency ratio (CR) of 0.0446. Both TOPSIS and SAW ranked plot A1 (Keprok Batu 55 II, 4-year stand) first and A2 (Keprok Batu 55 I, 15-year stand) last, with Spearman ρ = 0.8929 (p = 0.0068). The top and bottom ranks were held across all 10 sensitivity scenarios. The framework gives orchard managers a reproducible way to prioritize block-level soil intervention, marking A1 as the benchmark block and A2 as the priority for pH correction.