Abstract:
This thesis presents the development of a web-based procurement system designed
to improve the efficiency of purchase request (PR) and purchase order (PO) processes
within an organization. The system addresses common issues in manual procurement
workflows,such as approval delays, input errors, and difficulty in tracking inventory needs.
Built using the Next.js framework and MongoDB as the database, the system includes fea-
tures such as dynamic form fields, automatic ID generation, approval tracking, and real-
time data access from related collections like users, materials, and suppliers. These features
allow for more accurate data input, faster processing, and better control over procurement
activities.
The system was evaluated through functional and user acceptance testing. Results
show that the platform functions as expected, reduces processing time, and minimizes hu-
man error. Users also reported that the interface is intuitive and the overall workflow is
significantly more efficient compared to manual methods. By automating key procurement
tasks, the application supports better inventory management and contributes to a more re-
sponsive supply chain. The system provides a solid foundation for digital procurement in
small to medium-sized enterprises and is designed to be scalable for future needs such as
analytics, reporting, and integration with other business systems.
