Design and Development of Drug Formulation Classification Information System - Setiawan, Retno Agus; Al-Hakim, Rosyid Ridlo; Trivilia, Indah; Juniarti, Ulan (Universitas Trunojoyo Madura, 2024)
The increasing complexity of pharmaceutical management in pharmacies demands efficient systems to streamline drug classification and inventory control. As pharmacies handle a diverse range of formulations, including tablets, syrups, and injectables, the need for advanced systems that ensure accuracy, efficiency, and compliance is becoming increasingly evident. This study focuses on the design and development of a web-based Drug Formulation Classification Information System, specifically tailored to improve the management of drug formulations. The system was developed using a Rapid Application Development (RAD) approach with a focus on user-centered design, prioritizing the needs and experiences of end-users, particularly pharmacists and administrators. Core functionalities incorporated into the system include real-time inventory updates, advanced drug search and classification, and automated report generation to simplify daily operations. To evaluate system performance and user experience, usability testing was conducted with pharmacists from UHB Educational Pharmacy. Results indicated a high user satisfaction rate, with 85% of participants finding the system intuitive and easy to use. The system’s architecture features a clear and intuitive user interface that minimizes the learning curve, ensuring that both experienced and novice users can navigate the platform efficiently with minimal training. Feedback from testing aligned with the Technology Acceptance Model (TAM), emphasizing the importance of perceived ease of use and usefulness in driving system adoption and user satisfaction. This research contributes to the growing field of pharmacy informatics by offering a scalable, adaptable solution for pharmacy management, with potential for integration into larger healthcare systems. Future enhancements will focus on integrating predictive analytics and extending system capabilities to further support pharmaceutical operations and patient care.