Decision Support System for Choosing Online Learning Platforms Using the Complex Proportional Assessment Method

Abstract

Online learning platforms can be an alternative to learning outside of school that can help improve student academic achievement. To determine the right online learning platform, decision makers must seek information one by one about the services provided by the platform as well as its weaknesses and strengths. This makes it difficult to make a choice and takes a long time. This research aims to build a Decision Support System (DSS) for choosing an online learning platform by applying the Complex Proportional Assessment (COPRAS) approach to get the right decision and not take long. The COPRAS approach can produce optimal alternatives based on alternative analysis using alternative assumptions by offering utility judgments so that the attributes of each alternative are sorted by interval. Based on the results of the case study, Zenius obtained the highest utility score with a score of 100, followed by Ruangguru with a score of 86.19, Pahamify with a score of 84.34, and Quipper with a score of 68.67. The calculation results obtained from a system built by calculating manually displays the same acquisition value, this means that the system has produced an accurate calculation. On the results of usability testing using aspects including understanding, learnability, operability and interesting, the average score is 91% and is in the good category. This demonstrates how user-friendly and implementable the created system is.