Performance Comparison of Ontology and Certainty Factor Algorithm for the Diagnosis of Respiratory Diseases

DOI

10.2991/978-94-6463-926-1_65How to use a DOI?

Keywords

Certainty Factor; Diagnose; Ontology; Performance Comparison; Respiratory Disease

Abstract

The high prevalence of respiratory diseases in Indonesia has driven the government to implement various policies, such as strengthening primary healthcare services and promoting early detection programs, in order to reduce the morbidity and mortality associated with these diseases. As a solution to support early diagnosis, this study compares two approaches, namely Ontology and Certainty Factor (CF) Algorithm to diagnose respiratory disease symptoms. The method used involves the implementation of Ontology as a structured representation of medical knowledge, where relationships between symptoms, diseases, and other clinical concepts are formally defined to enable semantic reasoning. In parallel, the Certainty Factor (CF) approach is applied to incorporate expert knowledge by quantifying the degree of confidence or belief in a particular diagnosis based on observed symptoms. The results of the experiment show that both approaches are able to identify respiratory diseases, but with different results. Ontology is superior when compared to the CF algorithm. The CF algorithm is highly dependent on the accuracy of the certainty value provided by experts, making it susceptible to subjectivity. Meanwhile, the ontology approach produces a more consistent diagnosis because it is based on a systematic information structure. Based on these findings, Ontology is recommended as a more stable alternative for respiratory disease diagnosis support systems.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Selvia Ferdiana Kusuma
AU  - Andriana Wahyu Hapsari
AU  - Andhik Ampuh Yunanto
PY  - 2025
DA  - 2025/12/31
TI  - Performance Comparison of Ontology and Certainty Factor Algorithm for the Diagnosis of Respiratory Diseases
BT  - Proceedings of the International Conference on Applied Science and Technology on Engineering Science 2025 (iCAST-ES 2025)
PB  - Atlantis Press
SP  - 581
EP  - 591
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-926-1_65
DO  - 10.2991/978-94-6463-926-1_65
ID  - Kusuma2025
ER  -