Web-based Rabies Disease Diagnosis Expert System with Forward Chaining and Dempster Shafer Methods

Abstract

Rabies is a hazardous zoonotic disease that poses a significant threat to both animals and humans, as it can result in death. The disease is caused by a single-stranded RNA virus commonly found in infected animals' saliva, which can be transmitted to humans through bites. Although many people keep animals as pets, many lack adequate knowledge about the potential risks of rabies transmission. In Indonesia, most cases of rabies transmission to humans are caused by bites from infected dogs, followed by bites from monkeys and cats. The absence of an effective treatment for Rabies makes prevention and early diagnosis extremely important. One approach that could help manage the disease is creating an expert system for rabies diagnosis. The Rabies Disease Expert System is developed based on a needs analysis conducted through interviews with veterinarians to understand the classification of symptoms and the diagnostic process for Rabies. It's important to note that while the system is a valuable tool, it does have limitations and should not replace the role of a veterinarian. The system employs two critical methodologies: the Forward Chaining and Dempster-Shafer algorithms. These algorithms allow the system to trace the progression of symptoms and calculate the probability of a rabies infection. The system is an interactive platform where users—such as animal owners or medical professionals—can input observed symptoms in either animals or humans. Based on these inputs, the system provides a probable diagnosis. For example, the expert system might determine that a dog is in the 'Excitation Stage' of Rabies with a 54% confidence level. The integration of Forward Chaining and Dempster-Shafer methods ensures that the system continuously refines its diagnostic accuracy, aiming for a confidence level close to 100%. This expert system offers a promising tool to aid in the early detection and management of Rabies, potentially reducing the risk of widespread transmission.