Implementation of Employee Attendance with Face Recognition using Waterfall Method in Solo Technopark

Abstract

In the Business and Technology Incubator Division at Solo Technopark, the existing attendance system presents significant challenges, requiring employees to physically commute to a centralized attendance machine. This process not only reduces work efficiency and productivity but also disrupts the daily workflow, particularly under unfavorable weather conditions or during peak hours. To address these issues, this research proposes the development of an attendance system based on facial recognition technology. This system enables employees to register their attendance directly from their desks using the camera on their laptops, thereby conserving time, reducing physical contact, and enhancing overall workplace hygiene. The system's development follows the Waterfall Method, which is structured into five key stages: communication, planning, modeling, construction, and deployment. Unified Modeling Language (UML) was employed to design the system, which was subsequently implemented for real-time monitoring and management. The findings demonstrate a marked improvement in employee efficiency and productivity, validating the system's effectiveness in a practical setting. The study underscores the potential of facial recognition technology to streamline operational processes and improve the working environment within modern organizations.