This research aims to develop a web-based Sports Center reservation system integrated with an analytics dashboard to support decision-making and optimize the booking process. The urgency of this system development is based on the need for digitalization of booking services, which were previously done manually, prone to recording errors, and inefficient. The system is designed to allow real-time self-booking, with an interactive interface to select time slots and automatic detection to prevent double bookings. An additional feature includes a unique QR code provided as proof of booking, which can be scanned for attendance verification. The analytics dashboard presents data such as total revenue, number of bookings, most popular courts, availability rate, and booking trends over time. The development method uses the Waterfall model, consisting of analysis, design, implementation, testing, and maintenance stages. Testing results show that 87.04% of functional scenarios performed as expected, and security testing using OWASP ZAP identified some potential vulnerabilities, serving as a reference for system strengthening. The integration between the reservation system and the analytics dashboard has proven to enhance operational efficiency and the overall quality of the Sports Center's services.This research aims to develop a web-based Sports Center reservation system integrated with an analytics dashboard to support decision-making and optimize the booking process. The urgency of this system development is based on the need for digitalization of booking services, which were previously done manually, prone to recording errors, and inefficient. The system is designed to allow real-time self-booking, with an interactive interface to select time slots and automatic detection to prevent double bookings. An additional feature includes a unique QR code provided as proof of booking, which can be scanned for attendance verification. The analytics dashboard presents data such as total revenue, number of bookings, most popular courts, availability rate, and booking trends over time. The development method uses the Waterfall model, consisting of analysis, design, implementation, testing, and maintenance stages. Testing results show that 87.04% of functional scenarios performed as expected, and security testing using OWASP ZAP identified some potential vulnerabilities, serving as a reference for system strengthening. The integration between the reservation system and the analytics dashboard has proven to enhance operational efficiency and the overall quality of the Sports Center's services.
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