Sistem Pendukung Keputusan Pemilihan Aplikasi Belajar Online Menggunakan Metode Additive Ratio Assessment - Muhammad Bagir; Jefri Rahmadian; Ahmad Fatih Zahir; Irsyad Purbha Irwansyah (Journal of Information System Research (JOSH), 2023)
In the digital era, there are many educational platforms or learning applications that offer easy learning. However, with so many existing online learning applications, care is needed to choose one that suits your needs. To select an online learning application, users must look for information one by one on the profiles and features of existing online learning applications. This results in the difficulty and duration of making choices. This study aims to build a decision support system through the application of the Additive Ratio Assessment (ARAS) method for selecting online learning applications so that it can facilitate the selection and does not require a long time. The ARAS method looks for the best solution by comparing the utility function of each option with the optimum utility function value. Based on the existing case studies through the implementation of the ARAS method, the best alternative is Ruangguru (A4) with a score of 0.8819, followed by Kelaskita (A2) with a score of 0.8469, Zenius (A3) with a score of 0.8397, and Udemy (A1) with a value of 0.6282. The built-in decision support system produces valid calculations because the calculation results obtain the same value as the manual calculation results. Then, the usability test results produced an average value of 88.33%. This means that the system that is built is able to facilitate users in every functional area.