This research develops an online auction system utilizing the Django framework and Greedy algorithm to optimize the bidding process, addressing challenges in traditional auction systems such as geographical limitations, lack of transparency, and manual processes prone to errors. The study employs an Agile methodology with a Scrum approach, implementing a Model-View-Controller (MVC) architecture to separate business logic, presentation, and data management. The development of the auction application involves planning to identify system requirements, designing the architecture, implementing the backend/frontend, testing features and algorithms, deploying to the server, and conducting evaluation and adjustments based on feedback. Results demonstrate that the use of Django accelerates development and enhances system security, while the implementation of the Greedy algorithm successfully optimizes real-time bidding and winner selection processes. Key features developed include auction management, an automated bidding system, and secure payment integration.
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