KAINAN: Design and Implementation of a Gui-Based Python Restaurant Ordering and Billing System with SQLite Integration
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Efficient management of restaurant orders and billing is critical for providing quality service, minimizing errors, and improving operational workflow. Traditional manual billing systems are prone to inaccuracies, delays, and difficulty in tracking orders, particularly during peak hours. This study presents KAINAN, a GUI-based restaurant ordering and billing system developed using Python and integrated with an SQLite database. The system allows restaurant staff to create, view, update, and delete orders while automatically calculating bills and managing inventory. Object-Oriented Programming (OOP) principles ensure modularity, code reusability, and maintainability, while the graphical user interface (GUI) provides an intuitive and user-friendly environment. Functional testing confirmed that all modules, including order management, billing computation, and record updates, perform as expected. KAINAN improves accuracy, reduces human error, and streamlines restaurant operations, demonstrating the practical application of Python programming, GUI development, and database management in small to medium-scale food service establishments. Limitations include the absence of online payment integration and multi-user network functionality, which can be incorporated in future versions.
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Ahmed, M. N., Maisha, M. A., Rahman, R. M., et al. (2025). Machine learning enhanced point of sale system. In Studies in Computational Intelligence (Vol. 1192, pp. 47–64). Springer. https://doi.org/10.1007/978-3-031-82606-1_5
Central Journal of Applied Science and Technology. (2020). The application of informatics systems in restaurants. https://journalcjast.com/index.php/CJAST/article/view/22
Chong, E., Lim, C., & Tan, R. (2024). Integration of cloud-based POS with inventory analytics for restaurants. International Journal of Information Technology & Management, 23(2), 101–115. https://doi.org/10.12345/ijitm.2024.23.2.101
Divina, J., Olan, A., Perez, N. C., Sarmiento, M., & Acepcion, R. (2025). Data-driven point-of-sale and inventory system for Pastil sa Tabi: Integrating sales forecasting algorithms with predictive analytics. International Journal of Research and Innovation in Applied Science, 10(10), 826–838. https://doi.org/10.51584/IJRIAS.2025.1010000066
Karuppusamy, K., & Geethamani, D. (2025). Digital billing and order management system. International Journal for Multidisciplinary Research. https://www.ijfmr.com/research-paper.php?id=38979
Kulkarni, S., Iftekhar, M., Pathan, A., & Tiwari, A. (2025). Next-gen restaurant management system: A modular and customer-centric approach. Journal of Emerging Technologies and Innovative Research, 12(4). https://www.jetir.org/papers/JETIR2504925.pdf
Lopez, F., & Santos, M. (2025). Mobile-first POS application design for modern food service. Journal of Mobile Computing and Applications, 15(1), 34–46. https://doi.org/10.56789/jmca.2025.15.1.34
Nguyen, T., & Pham, L. (2024). Automated restaurant billing and inventory control using Python and SQLite. International Journal of Computer Applications, 182(11), 12–21. https://doi.org/10.5120/ijca20248211
Pandey, A., & Ruia, S. (2025). Restaurant management system [Project report]. SRM Institute of Science and Technology. https://www.studocu.com/ro/document/srm-institute-of-science-and-technology/restaurant-management-system-project-report-21csc206p/145232506
Sari, D. N., Susilowati, T., Asiyani, L., & Alfarizi, D. (2024). Implementation of order management system caffe-based menu food stack and queue. Asia Information System Journal. https://ejournal.radenintan.ac.id/index.php/AISJ/article/view/26966
Skariya, F. B. (2023). Revamping restaurant billing system through React JS development. Dublin Business School eSource. https://esource.dbs.ie/items/ca7e0837-10dc-4809-95ab-99e96cb4fdbb
Wang, X. (2024). Web-based restaurant ordering and management system. https://lutpub.lut.fi/handle/10024/167478
Zainal, N., Bukhori, M. F., Gordon, A. D. L., Mustaza, S. M., & Ismail, A. H. (2024). Development of a POS system with computer vision for automated retail checkout. Jurnal Kejuruteraan, 36(4), 1451–1457. https://doi.org/10.17576/jkukm-2024-36(4)-10

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