Pengembangan Aplikasi Web Pendeteksi Kondisi Ekspresi Pengguna E-Learning melalui Kamera - Akhmad Lazuardi; Fajar Pradana; Fitra Abdurrachman Bachtiar (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2022)
E-learning is the use of information and communication technology networks in teaching and learning. The COVID-19 pandemic is forcing educational entities to adapt to using e-learning. The virtual learning method has limitations in recognizing student expressions. Facial expressions cannot be used as a tool by lecturers to interpret students' understanding of online learning. Previous research has been able to build a system that can detect student emotions by detecting patterns of eyes, head, and facial expressions. Building a user facial expression monitoring system that is integrated with e-learning is one step to help educators detect student expressions online. The facial expression detector used is the face-api.js library. The data obtained from the face-api.js library is extracted and then sent to the database. Then the data stored in the database will be displayed on the admin page. The Hypersheets application will be a testing ground for integrating this facial expression detection system. The system development method uses the waterfall method. The developed system produces 4 functional requirements and 1 non-functional requirement. The unit test results get a 100% pass result and the validation test has 12 test cases and gets a 100% pass result. Web application compatibility testing using SortSite got no critical issues. And has a System Usability Scale value of 72.5 which is included in the category of having good usability. It is hoped that this system can help the Hypersheets application in detecting the user's facial expressions as a basis for monitoring the emotions of students who study with this application.