Multi-Criteria Analysis for Selecting Superior Rice Seeds Using SAW-AHP

Abstract

Rice is the staple food of the Indonesian population, and the quality of rice production largely depends on the selection of superior rice seeds. However, farmers often rely solely on manual observation and personal experience in seed selection, which can lead to crop failures due to suboptimal choices. This research aims to develop and implement a web-based Decision Support System (DSS) to assist farmers in selecting superior rice seeds using the Simple Additive Weighting (SAW) and Analytic Hierarchy Process (AHP) methods. The system evaluates nine criteria across seven seed alternatives, applying a 1–5 scale in SAW and a 1–9 pairwise comparison scale in AHP. The results indicate that HMS 700 ranks first in SAW with a score of 0.85, followed by IF16 at 0.75. In contrast, AHP identifies Inpari 42 as the top alternative with a priority value of 0.176, followed by IF17 at 0.161. The implementation of this system improves decision-making accuracy and contributes to increased agricultural productivity.