Abstract
The optimal selection of rice seedlings is a key factor in enhancing rice farming productivity during the rainy season. To achieve this goal, this research utilizes a Decision Support System (DSS) based on the MOORA Algorithm (Multi-Objective Optimization by Ratio Analysis). This study explores the selection of the best rice seedlings for the rainy season using the MOORA Algorithm. Evaluation criteria include plant height, harvesting time, tolerance to waterlogging, resistance to pests, disease resistance, and average yield per hectare. The research results identify Inpari 30 Ciherang Sub-1 (BP07) as the top choice for the rainy season with a Yi (max) value of 0.2998. This is followed by Inpara 4 (BP03) in second place with a Yi (max) value of 0.2913, and Ciherang (BP02) in third place with a Yi (max) value of 0.2849. We hope that the research findings will provide a positive contribution to improving agricultural productivity in the future and assisting farmers in better facing the challenges of the rainy season.
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