Enhancing School Data Security with Multi Factor Authentication

This study discusses the implementation of hybrid authentication methods to enhance school data security by combining token-based authentication and facial recognition. Currently, SMKN 4 Tanjungpinang uses a standalone application that stores sensitive student and teacher data. Although there have been no reports of data leaks, the current security relies solely on user passwords, which are considered inadequate against cyber attacks. Therefore, this study proposes the use of hybrid authentication to protect student data. The research methodology integrates token-based authentication and facial recognition to enhance the security of the student information system. The initial stage involves data collection and preprocessing, including gathering facial datasets to train facial recognition models and token datasets to test token-based authentication security. The experimental results show that token-based authentication enhances security by requiring a token before login, while facial recognition confirms user identity. Based on the experimental results, it can be concluded that a threshold value of 85% is obtained for facial recognition as a login method, and a higher threshold value needs to be set to increase confidence.