Multi-Criteria Decision Making Using the WASPAS Method in Webcam Selection Decision Support Systems

Abstract

To carry out all virtual or online activities, you need hardware that can support it, one of which is a webcam. Many webcam products issued by various electronics companies are compatible for laptops and computers. However, to make a webcam selection the user must know one by one the specifications of each webcam. This of course takes a long time to determine the right webcam. This study aims to implement the Multi-Criteria Decision Making (MCDM) approach with Aggregated Sum Product Assessment (WASPAS) on a webcam selection decision support system, in order to get the best, right and fast alternative. The WASPAS method can determine the best alternative through prioritization that is relevant to the weighting used. Based on the case studies conducted, the WASPAS method was able to determine the best webcam with the best alternative results, namely NYK Nemesis A96 with a value of 0.7053, followed by Aukey PC-LM7 with a value of 0.6826, JETE W2 with a value of 0.6799, Logitech C922 with a value of 0.6499 and Ausdom AF660 with a value 0.6271. Because the findings are identical to manual calculations, the created system generates legitimate WASPAS method calculations. Based on the tests carried out using the black-box testing approach, it shows that all the functions in the system can run as they should