Facial Recognition Using The Haar Cascade Classifier Method For Smart Absence - Reza Alamsyah; Indra Sidabutar (SEAN Institute, 2021)
The Processing student attendance data at STMIK Methodist Binjai plays an important role in implementing teaching and learning activities. The STMIK Methodist Binjai attendance system still uses stationery which is less efficient, thus affecting learning productivity. Therefore, a solution is needed to help with attendance problems so that attendance can be run efficiently and with fast computing. Namely by using Face Recognition technology for Smart Attendance using the haar cascade method in OpenCV. The results of the developed application can recognize faces with an accuracy rate of 81%. And users also manage data in the system and recording attendance data is stored in excel files