<![CDATA[Digital transformation in the healthcare sector, particularly within independent clinics, still faces various obstacles such as unintegrated medical record keeping, inefficient administrative processes, and limitations in clinical and operational data analysis. These conditions lead to poor service quality, potential medical errors, and suboptimal managerial decision-making. Therefore, an Electronic Medical Record (EMR) system is required that is not only digital but also smart and adaptive to the needs of independent clinics. This study aims to develop Smart-RME AI, an artificial intelligence-based smart electronic medical record system capable of integrating medical and operational data in real-time, supporting clinic service efficiency, and assisting clinical and managerial decision-making. This system is expected to improve operational effectiveness, medical recording accuracy, and the quality of healthcare services in independent clinics. The research method used is Design Science Research (DSR), which includes the stages of problem identification, system requirements formulation, design and development of the Smart-RME AI artifact, as well as system evaluation through functional and user feasibility testing. Artificial Intelligence implementation is applied for patient data analysis, visit patterns, and decision support recommendations based on historical data. The targeted outputs of this research include: (1) a Smart-RME AI system prototype ready for implementation in independent clinics, (2) a scientific article publication in a SINTA 3 accredited national journal, and (3) Intellectual Property Rights (IPR) in the form of a copyright for the Smart-RME AI software. This research is expected to make a tangible contribution to the development of health information systems and accelerate the digital transformation of independent clinic services.]]>
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