Web-Based Decision Support System for Superior Corn Seed Selection Using FMADM and AHP Algorithms - Donny Dwi Putra; Abdul Halim Hasugian (Ali Institute or Research and Publication, 2025)
Indonesia as an agricultural country still faces challenges in meeting national corn demand due to dependency on imports. One critical issue is the inaccurate selection of superior seeds that suit local conditions. This study aims to develop a web-based decision support system (DSS) for superior corn seed selection using the Fuzzy Multi-Attribute Decision Making (FMADM) algorithm combined with the Analytical Hierarchy Process (AHP) method.The research was conducted in Sei Tembo Village, Langkat Regency, with data obtained through observation, interviews with farmers, and literature review. The AHP method was applied to determine the weights of five criteria: water content, pest resistance, productivity, fruit size, and harvest time. Consistency testing produced a CR value of 0.028, indicating reliable weighting. The FMADM method was then used to rank 142 seed alternatives based on these weights.The results showed that the proposed system successfully ranked Srikandi Putih 1 (A32) as the best alternative with a score of 0.950, while Bima5 Bantimurung (A130) had the lowest score of 0.632. Productivity was identified as the dominant factor (weight = 0.484) in determining superior seeds.These findings demonstrate that the web-based DSS can improve accuracy and objectivity in seed selection, helping farmers reduce trial-and-error decisions. Practically, this system supports agricultural productivity improvement and contributes to strengthening national food security by reducing reliance on corn imports.