<![CDATA[Infectious diseases such as Dengue Fever (DHF), Tuberculosis (TB), and Malaria are still major health problems in Indonesia, especially in areas with limited medical resources such as Banyuputih Health Center. This study aims to develop an Android-based expert system that applies the Certainty Factor (CF) method to assist the diagnosis process of infectious diseases. The system is designed to calculate the level of confidence in a diagnosis based on symptoms inputted by the user, which are then combined with the confidence value of medical experts. There are 68 symptoms from 3 diseases with testing of 50 simulation cases used in this system, which were obtained through an interview process with medical personnel. Each symptom is given a CF value weight, which is then calculated in stages to produce the final diagnosis value. Testing was carried out using simulation data, and the implementation results showed that the system was able to provide high diagnostic accuracy, with a CF value of 0.9975 (99.75%) for Malaria cases, 0.997 (99.7%) for Tuberculosis, and 0.994 (99.4%) for DHF. The use of this system is expected to accelerate the diagnosis process, reduce the workload of medical personnel, and increase the efficiency of health services. This research contributes to the use of information technology as a supporting solution for digital transformation in the primary health care sector.]]>
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