<![CDATA[Heart disease is a leading cause of death in Indonesia, exacerbated by delayed diagnosis and lack of access to healthcare facilities. This study aimed to develop JantungIn, a cardiovascular risk assessment web platform using a microservices architecture. The system separated the user interface layer using Vue.js, server logic with Hapi.js, and a Supabase relational database. The novelty of this research lay in the real-time integration of a TensorFlow.js prediction model and a Vertex AI Dialogflow CX intelligent virtual assistant. System evaluation using the Black Box method covered positive and negative scenarios on core functionalities, including role authentication for doctors and patients, medical parameter validation, and medical history storage. The testing results showed that the software architecture successfully processed data exchange without functional errors. In conclusion, JantungIn was successfully implemented as a reliable medical decision support system to facilitate early detection of heart disease in the community.]]>
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