<![CDATA[Dengue Hemorrhagic Fever (DHF) poses a serious threat to public health, caused by the Dengue virus transmitted through Aedes aegypti or Aedes albopictus mosquitoes. DHF can affect individuals of all age groups, especially children, with a mortality rate reaching 25% among children, as noted by the World Health Organization (WHO). Despite a decrease in DHF cases in 2020, the numbers remain high, presenting a significant issue in Indonesia, particularly in Kota Medan. RSUD Dr. PIRNGADI in Kota Medan is one of the hospitals addressing DHF cases. The primary challenge faced is the substantial increase in DHF patients in 2020, leading to a decrease in the effectiveness of patient care and an accumulation of administrative registration issues. Currently, there is no specific predictive system or research on DHF at RSUD Dr. PIRNGADI. This research aims to integrate the Naïve Bayes Algorithm and a website for early detection of DHF at RSUD Dr. PIRNGADI. Data on DHF symptoms are collected through patient medical records, and the Naïve Bayes Algorithm is employed to predict the likelihood of DHF. The detection system will be linked to an API and integrated into the RSUD Dr. PIRNGADI website, enabling users to conduct online DHF detection by entering patient symptoms. With this research, the goal is to contribute to enhancing the management of DHF cases at RSUD Dr. PIRNGADI, improving the efficiency of patient care, and providing a solution for the increasing number of DHF cases. The findings of this research can also serve as a foundation for developing similar systems in other hospitals and contribute to more effective efforts in preventing and controlling DHF]]>
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