The management of student attendance in a university is one of the most important indicators to be taken into account, as it contributes to the quality of the educational system. The university will usually have minimum attendance requirements for the exam. The manual attendance system, which has been known since ancient times, has proven to be less effective and accurate. In recent research, several modern approaches, such as the attendance system based on IoT and Artificial Intelligence, have shown significant growth. Therefore, this research was conducted to find out how effective, efficient, and accurate the use of facial biometrics in the student attendance system is through a systematic review approach (SLR). The insignificant results show that the implementation of this technology is proven to be more effective and accurate compared to the manual attendance system. However, this technology still has some external factors that can affect the reliability of the system, so additional steps or strategies are needed for the system to recognize faces correctly.