I. Gede, I. Sudipa, Jurnal, Hamid Wijaya, Rhaishudin Jafar Rumandan, H. Taher, Jalan Kebun Cengkeh, Batu Merah, Kec. Sirimau, Maluku Indonesia Kota Ambon
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引用次数: 0
Abstract
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.
优化利用家庭庭院是通过蔬菜种植提高农业粮食安全的努力之一。蔬菜种子产品的数量导致购买蔬菜种子的人首先要查找每种蔬菜种子的信息,从而需要很长时间才能做出决定。本研究旨在将多属性决策(MADM)与总产品评估(WASPAS)方法应用于蔬菜种子选择决策支持系统,以获得最适合您需求的选择方案。WASPAS方法通过优化评价,选择最高和最低的值,从而获得最佳方案,具有求解多属性的能力。基于案例研究,WASPAS方法能够确定最好的蔬菜种子最好的选择的结果,即认识你种子Brokoli F1 (A2)气值为0.7854,然后跟着一个替代Infarm Benih Kangkung (A1)气值0,7710,每日农场Sawi Putih (A3)气值为0.7330,米拉Mentimun Hibrida F1 (A4)气值为0.7225和Benihpedia Daun霸王(A5)气值为0.5992。所开发的系统产生了有效的WASPAS方法,因为结果与人工计算没有什么不同。此外,黑盒测试结果表明,所开发的系统运行良好。