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Optimizing the use of home yards is one of the efforts to improve food security in agriculture through vegetable cultivation. The number of vegetable seed products causes someone who will buy vegetable seeds to first seek information about each vegetable seed, thus taking a long time to make a decision. This study aims to implement the Multi-Attribute Decision Making (MADM) approach with Aggregated Sum Product Assessment (WASPAS) on a vegetable seed selection decision support system, in order to obtain the best alternative that suits your needs. The WASPAS method has the ability to solve multi-attribute by optimizing the assessment for selecting the highest and lowest values in obtaining the best alternative. Based on the case studies conducted, the WASPAS method was able to determine the best vegetable seeds with the best alternative results, namely Known You Seed Brokoli F1 (A2) with a Qi value of 0.7854, then followed by an alternative to Infarm Benih Kangkung (A1) with a Qi value of 0, 7710, Daily Farm Sawi Putih (A3) with a Qi value of 0.7330, Mira Mentimun Hibrida F1 (A4) with a Qi value of 0.7225 and Benihpedia Daun Bawang (A5) with a Qi value of 0.5992. The developed system produces a valid WASPAS method, because the results are no different from manual calculations. In addition, the results of black-box testing show that the developed system has been running well. |
