AutoRentPro: Design and Implementation of a GUI-Based Python Car Rental Management System with SQLite Integration

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Doploso, John Abel S.
Hombrebueno, Jonathan D.
Honrado, Franz Gabriel G.
Magalona, Aron Luis T.
Montero, James Adrian D.
Aldepolla, Patrick Sean H.
Cariaga, John Kenth S.
Engr. Fabro, Meshelle N.

The management of car rental operations, including vehicle inventory, customer reservations, and rental transactions, is often prone to errors when conducted manually. Delays in booking, inaccurate record-keeping, and inefficient tracking of vehicle availability can lead to customer dissatisfaction and operational inefficiency. This study presents AutoRentPro, a GUI-based Python Car Rental Management System integrated with an SQLite database to automate rental processes and enhance data accuracy. The system allows administrators to manage vehicle information, process customer bookings, track rental transactions, and generate reports on vehicle usage and availability. Object-Oriented Programming (OOP) principles were applied to ensure modularity, scalability, and maintainability of the code. Functional testing confirmed that the system successfully handles vehicle management, customer registration, booking processing, and report generation, while the GUI facilitates an intuitive user experience. AutoRentPro improves efficiency, reduces human error, and provides a reliable platform for managing car rental operations in small to medium-sized enterprises. Limitations include the absence of online payment integration and fleet telematics, which may be considered for future enhancement.

AutoRentPro: Design and Implementation of a GUI-Based Python Car Rental Management System with SQLite Integration. (2026). International Journal of Latest Technology in Engineering Management & Applied Science, 15(6), 1242-1259. https://doi.org/10.51583/IJLTEMAS.2026.150600089

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AutoRentPro: Design and Implementation of a GUI-Based Python Car Rental Management System with SQLite Integration. (2026). International Journal of Latest Technology in Engineering Management & Applied Science, 15(6), 1242-1259. https://doi.org/10.51583/IJLTEMAS.2026.150600089