Current developments in information technology are driving the digitalization of human resource management systems to improve operational efficiency and data accuracy. Cafe Magi, a culinary business with many operational employees, still faces challenges due to its manual attendance system, which uses verbal reports. This conventional system triggers various crucial problems, such as a high risk of data loss, vulnerability to attendance manipulation, long processing times for recapitulations, and difficulty in real-time monitoring by the business owner. To address these issues, this study aims to develop a web-based employee attendance application that is automated, more structured, and efficient. In addition, this system integrates face recognition technology and Global Positioning System (GPS) tracking features to minimize employee fraud. The software development method applied in this study is the Waterfall method, which includes the stages of needs analysis, design, implementation, and testing in a sequential and systematic manner. The result of this study is a web-based attendance application that has been successfully built and tested according to the partner's needs. The integration of face recognition and GPS features has proven effective in preventing attendance data manipulation by operational employees. In conclusion, the implementation of this attendance application has digitized the attendance management system at Cafe Magi, accelerated attendance data processing, reduced human error, and facilitated management's real-time monitoring and control of employee performance.