MOORA and SAW Methods for Selecting Optimal Oil Palm Fertiliser - Sinambela, Surya Pranata Rejeki; Khairani, Mufida (Journal of Technology and Computer, 2025)
Oil palm (Elaeis guineensis) is an important commodity for Indonesia’s economy; therefore, fertilizer selection during the nursery stage plays a crucial role in determining the quality and productivity of the plants. This study aims to develop a web-based Decision Support System (DSS) by applying the Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) and Simple Additive Weighting (SAW) methods to determine the best fertilizer for the optimal growth of oil palm seedlings. The evaluation was conducted on ten fertilizer alternatives using five criteria, namely price, availability, ease of application, growth effectiveness, and solubility. The results of the study show that Urea Pupuk Kujang ranked first in both methods, with a MOORA score of 0.2084 and a SAW score of 0.8333. These findings indicate that the application of MOORA and SAW can support more objective, efficient, and reliable decision-making in selecting the best fertilizer for oil palm seedlings.