Application of Hybrid Expert System Method for Web-Based Diagnosis of Diseases Caused by Cigarettes
Penerapan Metode Hybrid Sistem Pakar Untuk Diagnosis Penyakit Yang Disebabkan Oleh Rokok Berbasis Web
DOI:
https://doi.org/10.21070/ups.10112Keywords:
Expert System, Certainty Factor, Forward Chaining, Smoking-Related Diseases, DiagnosisAbstract
Smoking is a widespread habit that poses serious health risks to both active and passive smokers. Limited public awareness and restricted access to early medical diagnosis often cause smoking-related diseases to be detected at later stages. This study develops a web-based expert system to support early diagnosis of diseases caused by smoking. The system applies a hybrid approach combining Forward Chaining and Certainty Factor, where Forward Chaining is used to infer diagnoses and Certainty Factor calculates confidence levels based on selected symptoms. The system is developed using React JS with an SQLite database and tested through Black Box Testing to ensure proper functionality. The results show that the system can diagnose eight types of smoking-related diseases based on 33 symptoms, providing diagnostic confidence percentages and initial treatment recommendations. This expert system serves as a supportive tool before further medical examination by healthcare professionals.
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