Development of Radiology Management System for Digital-Based Operational Implementation of Officer Schedules

Background: The scheduling of work of health workers, especially radiographers in type B hospitals, is a complex challenge due to the variety of radiology modalities, variations in the number of human resources, and the provisions of working hours regulations from the Ministry of Health of the Republic of Indonesia. Manual scheduling that is still in use tends to cause workload inequality, conflicts between employees, and operational inefficiencies. Objective: This study aims to design and develop an Artificial Intelligence (AI)-based radiographer shift scheduling system that is able to prepare work schedules automatically, fairly, flexibly, and integratedly, in accordance with hospital service regulations and needs. Research Method: This type of research is Research and Development (R&D). The development process is carried out through the stages of needs analysis, designing Python and Flask-based systems, simulating tests on data, and expert validation then the data collected and described from the initial mapping and also mapping potential problem-solving. Results: The system successfully manages morning, noon, night, and holiday shift schedules based on competence, fair rotation, and maximum working hours provisions. By showing a significant difference between user perceptions before and after using the system, which reflects improved efficiency, fairness, and ease of access to schedules. Respondents expressed satisfaction with the override feature and integrated notifications. Conclusion: The development of an AI-based radiographer shift scheduling system has proven to be feasible and effective in overcoming managerial problems of work scheduling in hospitals. This system is able to increase efficiency, transparency, and user satisfaction, and has the potential to be widely applied to various types of hospitals in Indonesia.