A SMART-Based Multi-Criteria Decision Support System for Oil Palm Fertilizer Selection - Wahyu, Meidy Fajar; Mahfudza, Liza Wardhatul (Komunitas Dosen Indonesia, 2026)
The selection of appropriate fertilizers is a critical factor influencing productivity and cost efficiency in oil palm plantations. In practice, fertilizer decisions are frequently based on subjective experience and fragmented information, while existing decision approaches rarely integrate agronomic suitability, economic considerations, and local operational constraints within a single transparent framework. This gap limits consistent and evidence-based fertilizer selection, particularly for plantation managers and smallholders operating under price volatility and uneven input availability. To address this limitation, this study proposes a multi-criteria Decision Support System (DSS) based on the Simple Multi-Attribute Rating Technique (SMART) for fertilizer selection in oil palm cultivation. The proposed model incorporates four evaluation criteria: water solubility, price, expert recommendation, and local availability. Criterion weights were determined through expert consultation, and seven fertilizer alternatives were evaluated using normalized utility values and weighted aggregation to generate preference rankings. The results show that Phonska fertilizer achieved the highest preference score, followed by Pelangi and Mutiara fertilizers, indicating that SMART effectively structures multi-dimensional decision problems into interpretable outcomes. To operationalize the model, a web-based DSS was developed to support automated computation and user interaction. Functional and logical testing confirmed the accuracy and reliability of the system. From a practical perspective, the DSS provides an accessible and transparent tool that supports plantation managers and smallholder farmers in selecting fertilizers that balance agronomic performance, economic feasibility, and local availability. Overall, this study demonstrates the applicability of a lightweight, SMART-based DSS for improving rational fertilizer management decisions in oil palm plantations.