Decision Support System for Optimizing the Selection of the Best Rice Seeds Using the MOORA Method

Abstract

This study aims to develop a Decision Support System (DSS) based on the Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) method to assist farmers in selecting the best rice seeds in a systematic, objective, and data-driven manner. The case study was conducted in Cengkeh Turi Subdistrict, Binjai City, considering ten key criteria such as productivity, pest resistance, grain quality, and seed availability in the market. A quantitative-descriptive approach was used, with data obtained from field observations, interviews, documentation, and relevant literature. The system was built using Python and the Streamlit framework to create an interactive web-based application. The MOORA calculation results showed that the Sidenok (Rambutan) rice variety achieved the highest optimization score (Yi) of 0.2127. The system not only provides accurate technical recommendations but also helps farmers understand the selection process through a user-friendly interface and clear visualizations. System validation showed consistency between manual and system-generated calculations, and local farmers provided positive feedback on usability and result reliability. These findings demonstrate the effectiveness of the MOORA method in local agricultural decision-making and highlight its potential for further development through the integration of climate-based predictive features. The system is expected to contribute to precision agriculture innovation and support sustainable national food security efforts.