Classification of Pneumonia Severity in Children Using the Fuzzy K-Nearest Neighbor Method Based on Patient Clinical Data - Rahmat Thaib; Betrisandi Betrisandi (Jambura Journal of Electrical and Electronics Engineering, 2026)
Pneumonia is one of the most deadly acute respiratory infections in children, especially in the toddler age group. Indonesia ranks eighth among 15 countries with the highest pneumonia mortality rate, namely 22,000 toddler deaths per year. Pneumonia can be caused by various microorganisms such as viruses, fungi, and bacteria. The occurrence of pneumonia is characterized by symptoms of cough and/or difficulty breathing such as rapid breathing and lower chest wall indrawing. The diagnosis of pneumonia is generally based on a combination of clinical symptoms such as fever, cough, rapid breathing, and physical examination results such as physical or radiological, however, the diagnostic process often encounters obstacles, such as limited trained medical personnel, limited diagnostic tools and subjectivity in assessing symptoms, especially in children who are not yet able to communicate their complaints clearly. This study aims to classify pneumonia based on symptoms and severity, namely severe pneumonia and mild pneumonia in children to assist medical personnel in making more accurate and efficient decisions. The results of this study indicate that the Fuzzy K-Nearest Neighbor method with k=3 and m=2 produces an accuracy of 62.67%, precision of 65.91%, recall of 69.05%, F1-Score of 67.44%, and a deviation of ±8.00% in classifying pneumonia in children.