<![CDATA[Mood disorders in children are a serious mental health issue that can have long-term impacts on their emotional, social, and academic development. In Indonesia, the limited availability of mental health professionals, especially in remote areas, hinders the process of fast and accurate diagnosis. Manual diagnosis of mood disorders in children often faces challenges in terms of time, resources, and professional expertise, creating a need for an effective solution to support medical practitioners. This research aims to develop a web-based expert system to detect mood disorders in children using the Dempster-Shafer Theory (DST) approach. DST is chosen as the primary method due to its ability to process ambiguous or incomplete information, enabling the integration of multiple pieces of evidence to generate accurate decisions. The system allows users to perform diagnoses based on input symptoms, accompanied by analysis results and follow-up recommendations. The expert system is developed as a web-based platform to optimize accessibility, allowing users to easily carry out the diagnosis process without time and location constraints. Evaluation of the system shows an accuracy rate of 92.5%, validating the effectiveness of DST in mood disorder diagnosis. This research contributes to supporting early detection of children's mental health issues and facilitates the identification of mood disorders based on the symptoms experienced.]]>
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