<![CDATA[Neonatal sepsis is a condition caused by bacterial infection in infants during the neonatal period and is one of the leading causes of newborn mortality in many countries around the world, including Indonesia. Indonesia ranks fifth among Southeast Asian countries with the highest neonatal mortality rate. Most of these deaths can essentially be prevented through effective prevention, early diagnosis, and prompt treatment and care. This study aims to develop a web-based expert system application designed to perform early detection of neonatal sepsis, capable of storing and managing knowledge similar to that of a medical expert. The Certainty Factor method is used to calculate and measure the level of confidence in the diagnostic results, while the Forward Chaining method serves as the reasoning mechanism to generate conclusions based on the symptoms selected by the user. The expert system provides comprehensive information on symptoms, treatment steps, care procedures, and medical advice, thereby assisting both healthcare professionals and the public in identifying sepsis risks at an early stage. The testing results show that the expert system can provide a diagnostic confidence level of 94.77%, indicating the system’s accuracy in supporting clinical decision-making and its potential to help reduce neonatal mortality rates.]]>
Copyrights © 2026
