<![CDATA[The selection of superior rice seeds is a crucial stage in improving agricultural productivity in Indonesia. However, farmers often select seeds subjectively without systematically considering important factors. To address this issue, this study designs and develops a Decision Support System (DSS) based on the Simple Additive Weighting (SAW) method to assist farmers in selecting the best rice seeds using six criteria: pest resistance, harvest age, amylose content, yield, irrigation water efficiency, and rice texture. Data were collected through interviews with five farmers in Mangir Lor. The results showed that the rice variety Inpari 32 achieved the highest score of 0.87, thus recommended as the best alternative. The SAW method proved effective in managing multicriteria data and producing objective and accurate results. This DSS is expected to serve as a practical decision-making tool for farmers in selecting high-quality rice seeds and contribute to the achievement of sustainable national food security.]]>
Copyrights © 2025
