Multi-criteria decision making using weighted aggregated sum product assessment in corn seed selection system - Hendra Mayatopani (Institute of Computer Science (IOCS), 2023)
Corn is one of the seven national strategic commodities developed by the government. The role of corn in the national industry is so great that the process of cross-breeding is often carried out in order to obtain superior varieties. Given the important role of corn in Indonesian agriculture, it is normal for corn seeds to be scattered in the market. For this reason, corn farmers or someone who wants to grow corn must be careful to choose the right corn seeds for their needs and what they want. This study aims to implement the Multi-Criteria Decision Making (MCDM) approach with Weighted Aggregated Sum Product Assessment (WASPAS) on a corn seed selection decision support system, in order to obtain the best alternative according to the needs of several alternatives and certain criteria. The WASPAS method is able to solve multi-criteria problems by optimizing the assessment for selecting the highest and lowest values to get the best alternative. The DSS developed is based on a website, with the main features including managing criteria and weight data, alternative data, conducting alternative assessments, calculating processes using the WASPAS method and displaying the best alternative in the form of ranking. In addition, the developed system produces valid WASPAS method calculations, because the results are in accordance with manual calculations. Based on the tests carried out with the black-box testing approach, it shows that the system built has been running well.