<![CDATA[Purpose: This community service program project developed an Artificial Intelligence-based expert system to support integrated medical services at the Bertha Primary Care Clinic in Medan by improving diagnostic accuracy, decision-making, and patient care quality. Methodology: The system was developed using a knowledge-based expert system with an inference mechanism that involved medical staff and patient data. Data collection included observations, interviews, medical record analyses, and case simulation testing. Results: The Artificial Intelligence based expert system improved the efficiency and accuracy of patient care by providing preliminary diagnostic recommendations, reducing patient wait times, and assisting medical staff in decision-making. Conclusions: The expert system effectively supports integrated medical care, enhances service quality, optimizes healthcare workflows, and demonstrates strong potential for primary healthcare facilities. Limitations: The system depends on the completeness and accuracy of the knowledge base, as well as the quality of the input data provided by users. Incomplete, outdated, or inaccurate data may affect the reliability of the system’s recommendations. In addition, testing was conducted only in one clinic, which limits the generalizability of the findings to other healthcare settings with different patient characteristics, operational procedures, and clinical needs. Contributions: This study offers a practical AI-based solution for primary healthcare services and demonstrates the potential of expert systems for medical decision support.]]>
