Perbandingan Metode Dempster Shafer Dan Teorema Bayes Untuk Mendeteksi Penyakit Ensefalitis

 M. Mustaqim (Universitas Nasional, Jakarta, Indonesia)
 Galih Rakasiwi (Universitas Nasional, Jakarta, Indonesia)
 (*)Agus Iskandar Mail (Universitas Nasional, Jakarta, Indonesia)

(*) Corresponding Author

Submitted: January 13, 2024; Published: January 30, 2024

Abstract

The aim of this study was to evaluate how well Bayes' Theorem and the Dempster-Shafer Method identify encephalitis. Inflammation of the brain, or encephalitis, can be caused by several things, such as bacterial or viral diseases. The main aim of this study was to assess how well both approaches perform in identifying this disease using clinical data. The main problem faced in detecting encephalitis is the complexity of the variations in symptoms and causal factors. This research focuses on analyzing clinical data of encephalitis patients, including medical history, laboratory test results, and clinical symptoms. The Dempster-Shafer method, a belief theory approach that allows the integration of information from uncertain sources, will be compared with Bayes' Theorem, a classical statistical approach frequently used in medical diagnostics. The research method involves collecting clinical data from medical records of patients diagnosed with encephalitis. This data will then be analyzed using the Dempster-Shafer Method and Bayes' Theorem to compare their accuracy in detecting disease. In addition, evaluation of method performance will also be carried out by comparing the sensitivity, specificity, and positive and negative predictive values of each method. The results of this research are expected to provide better insight into the effectiveness of the Dempster-Shafer Method and Bayes' Theorem in detecting encephalitis. The implications of these findings can be used to improve existing diagnostic methods and increase the ability of early detection of this disease. This research has the potential to make an important contribution to the development of the field of diagnostic medicine and can help medical practitioners make better decisions in the management of encephalitis patients. Using the Dempster Shafer method, the encephalitis diagnosis rate reached 99.8%, while applying Bayes' Theorem gave a diagnosis rate of only 3.5%. From these results it can be concluded that the application of Dempster Shafer is more powerful and provides a higher level of confidence in the encephalitis diagnosis process compared to the Bayes Theorem method.

Keywords


Expert System; Dempster Shafer Method; Bayes Theorem Method; Encephalitis Disease

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