Smart Online Class Monitoring Service Design

Distance learning is a learning method used during the COVID-19 pandemic. In implementing distance learning, the lecturer uses two learning approaches, namely synchronous and asynchronous learning. Each of these learning approaches cannot be separated from challenges and obstacles from the lecturer and students. One of them is distance learning causes students to become less focused, even absent from the learning process. In this study, a virtual classroom monitoring service will be designed to help teachers monitor and evaluate the learning process with a synchronous approach. A virtual classroom monitoring service will require participants to meet face-to-face via video teleconferencing. The solution offered is to utilize Artificial Intelligence (AI) technology in the form of face detection, which will monitor the presence and facial expressions of learning participants through a camera installed on their computer. The research methods used and mapped are Design Research Methodology as the primary methodological basis and System Engineering as a supporting methodology for the Prescriptive Study stage. The result of this research is that the design of the smart online class monitoring service is successful by using a combination of two methodologies which consists of two applications, namely a desktop app for students and a website application for teachers. This service system can make distance learning with a synchronous approach more effective.