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All Journal Building of Informatics, Technology and Science Jurnal Pengabdian Masyarakat Gemilang (JPMG) Jurnal Bangun Abdimas
Bobbi Kurniawan Nasution, Muhammad
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Arts Computer Science & IT Economics, Econometrics & Finance Education Engineering Materials Science & Nanotechnology Public Health Social Sciences Other

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Journal : Building of Informatics, Technology and Science

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Studi Perbandingan Metode Dempster-Shafer dan Teorema Bayes dalam Sistem Pakar Diagnosa Penyakit Sistem Pernapasan Kusmanto, Kusmanto; Esabella, Shinta; Karim, Abdul; Bobbi Kurniawan Nasution, Muhammad; Hidayatullah, Muhammad
Building of Informatics, Technology and Science (BITS) Vol 7 No 1 (2025): June (2025)
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i1.7317

Abstract

Respiratory system disease diagnosis often faces challenges in ensuring the accuracy of results due to the complexity of overlapping symptoms. In particular, a method is needed that is able to handle data uncertainty and utilize existing evidence optimally. This study aims to compare two methods, namely Bayes' Theorem and Dempster-Shafer, in diagnosing three types of respiratory diseases: Asthma, Tuberculosis, and Bronchitis. The solution is done by analyzing the percentage of confidence produced by each method based on symptom data. The results show that Bayes' Theorem produces the highest confidence for Tuberculosis (74.92%), while Dempster-Shafer provides the highest confidence for Bronchitis (80%). This comparison indicates that the selection of methods must be adjusted to the characteristics of the data and the needs of the analysis. This study contributes to providing insight into the advantages and disadvantages of each method, which can be used as a reference in developing a more accurate disease diagnosis decision support system.
Co-Authors Abdul Karim Abdul Karim Febriani, Budi Hidayatullah, Muhammad Kusmanto Kusmanto Kusmanto Shinta Esabella Suryadi, Sudi