Decision support system in predicting pneumonia transmission in toddlers based on life patterns

Abstract

The increasingly widespread spread of pneumonia during the Covid-19 pandemic that attacks children, especially toddlers, has caused the under-five mortality rate (IMR) to increase. Pneumonia is the most worrying thing for parents because it is an acute respiratory disease that attacks the lungs due to the lack of special health information for toddlers that parents get about lifestyle during the Covid-19 pandemic. With the health information from the government for toddlers through the media, especially in improving a healthy lifestyle, it is expected to minimize the transmission of pneumonia. The problem that occurs in the transmission of pneumonia among the general public is air pollution by the presence of bacteria, viruses, and fungi or parasites and the most common types of bacteria attack Streptococcus Pneumonia and Haemophilus Influenzae Virus type b (Hib). The weakening of the condition of children with this disease due to lack of adequate oxygen intake so that children will feel pain in the esophagusarea when breathing. To be able to predict the transmission of pneumonia in toddlers based on lifestyle, the Fuzzy Multiple Attribute Decision Making (Fuzzy MADM) method through a Decision Support System (DSS) is used.