Design and Implementation of Student Attendance System Based on Face Recognition by Haar-Like Features Methods

The attendance system is very important for every organization because it can track the people involved in it to maximize their performance. There are various methods in applying the presence system, including using faces, fingerprints, iris, sounds, and so forth. The ability to manage student attendance during attendance is a challenge because errors often occur and take a long time. In the traditional system, it is usually done by signing a piece of paper that is carried by the lecturer in each class session. This research presents the development of student attendance systems using facial recognition patterns with the Haar-like features method. With this method, it can overcome several manual system problems and provide solutions such as limits on the delay for lecturers and students, as well as minimizing the possibility of fraud in the attendance system. In the Administration section with this model can be automated to save time and resources needed to enter attendance data. After the proposed model was implemented, it was proven to reduce the time needed to enter attendance data from 6 until 8 days to only 3 to 4 days.