WEB-BASED CLIMATE CHANGE DISEASE DIAGNOSIS EXPERT SYSTEM USING FORWARD CHAINING METHOD - Edwina Rudyarti; Uci Sulandari; Yunita Sari Purba (Postgraduate, University of Mataram, 2025)
Climate change in Indonesia has a significant impact on public health due to extreme weather that triggers various diseases, such as diarrhea, influenza, pruritus, ARI, malnutrition, and stress. This study aims to design and implement a web-based expert system with the Forward Chaining method to help the community make early diagnoses of diseases affected by climate change. The research method uses a descriptive design and a cross-sectional approach. The location of the study was carried out at the Mekarmukti Health Center, North Cikarang with a sample consisting of 100 patients who experienced symptoms of climate-related diseases and were selected using the Simple Random Sampling technique. Data were collected through observation, interviews, and literature studies, then the questionnaire data were analyzed using the Chi Square test to evaluate the level of user satisfaction with the expert system. The results of the study showed that this system was able to effectively diagnose diseases due to climate change such as pruritus (P01), diarrhea (P02), and influenza (P03) which are commonly found in the Cikarang area. This system has proven to be useful as an information technology innovation that provides accurate symptom and diagnosis information like an expert. In conclusion, this expert system can be widely accessed by the public and functions as an early diagnosis aid in health care facilities in dealing with diseases impacted by climate change.