Published: 2025-08-01
Development and Evaluation of an Expert System for the Early Diagnosis of Dental Diseases
DOI: 10.35870/ijsecs.v5i2.4500
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Abstract
Dental diseases, such as caries, periodontitis, and gingivitis, affect public health worldwide, especially in regions where healthcare access remains restricted. The study develops an expert system for early dental disease diagnosis using Forward Chaining and Certainty Factor methods. The system overcomes deficiencies found in previous approaches, such as Naive Bayes and Dempster-Shafer, which demonstrate insufficient accuracy and unclear result interpretation. The developed expert system incorporates a knowledge base containing 7 diseases, 40 symptoms, and 7 diagnostic rules. Forward Chaining enables inference of potential diagnoses from reported symptoms, while the Certainty Factor evaluates diagnostic reliability by calculating confidence levels. System evaluation through Black Box testing achieved 92% diagnostic accuracy, and usability assessments revealed 85% user satisfaction rates, demonstrating that the system proves reliable, accurate, and accessible. Research findings indicate the expert system offers viable solutions for improving dental disease diagnosis in underserved and remote areas, potentially enhancing oral health outcomes through early detection and prompt intervention.
Keywords
Expert System ; Dental Disease Diagnosis ; Forward Chaining ; Certainty Factor
Article Information
This article has been peer-reviewed and published in the International Journal Software Engineering and Computer Science (IJSECS). The content is available under the terms of the Creative Commons Attribution 4.0 International License.
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Issue: Vol. 5 No. 2 (2025)
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Section: Articles
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Published: %750 %e, %2025
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License: CC BY 4.0
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Copyright: © 2025 Authors
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DOI: 10.35870/ijsecs.v5i2.4500
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Eko Purwanto
Faculty of Computer Science, Universitas Duta Bangsa Surakarta, Surakarta City, Central Java Province, Indonesia
Devi Pramita Sari
Faculty of Health Science, Universitas Duta Bangsa Surakarta, Surakarta City, Central Java Province, Indonesia
Farahwahida Mohd
Malaysian Institute Information Technology, Universiti Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia
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Mirzayev, F., et al. (2021). World health organization recommendations on the treatment of drug-resistant tuberculosis, 2020 update. European Respiratory Journal, 57(6). https://doi.org/10.1183/13993003.03300-2020
-
Clark, S. D. (2024). Spatial disparities in access to NHS dentistry: a neighbourhood-level analysis in England. European Journal of Public Health. https://doi.org/10.1093/eurpub/ckae099
-
Kottapalli, P. (2023). Barriers to healthcare across rural communities-testing telehealth as an alternative model of healthcare service delivery. Journal of Medical Healthcare, 5(9), 1-3. https://doi.org/10.47363/jmhc/2023(5)271
-
Osadolor, O. O., Osadolor, A. J., Osadolor, O. O., Enabulele, E., Akaji, E. A., & Odiowaya, D. E. (2022). Access to health services and health inequalities in remote and rural areas. Janaki Medical College Journal of Medical Sciences, 10(2), 70-74. https://doi.org/10.3126/jmcjms.v10i2.47868
-
Al-Buhaisi, D., Karami, S., & Gomaa, N. (2024). The role of teledentistry in improving oral health outcomes and access to dental care: An umbrella review. Journal of Oral Rehabilitation, 2375-2389. https://doi.org/10.1111/joor.13836
-
Kumar, A., Dogra, N., Sarita, Bhatia, S., & Sidhu, M. S. (2024). Handbook of intelligent and sustainable smart dentistry. https://doi.org/10.1201/9781003404934
-
Arefin, S. (2024). The role of artificial intelligence in dental diagnosis. International Journal of Scientific Research and Management, 35(1), 1114-1118. https://doi.org/10.1016/j.scrs.2024.101007
-
Lodha, N., Pal, A., Das, S., Roy, S., Chakraborty, S., & Pandey, S. K. (2023). Deep learning empowered IoT toothbrush: A paradigm shift in dental health monitoring. 1, 1-6. https://doi.org/10.1109/icaiihi57871.2023.10489375
-
Hashemikamangar, S. S., Sooratgar, A., Khayamzadeh, M., Momeni, S. N., Safaei, A., & Behniafar, B. (2025). Design and evaluation of screening and self-care (mobile) application for oral and dental problems and emergencies. Journal of Oral Biology and Craniofacial Research, 15(1), 113-122. https://doi.org/10.1016/j.jobcr.2024.12.016
-
Kritsada, C., Somsak, S., Srisuwan, P., & Anong, B. (2023). Enhancing early detection of gingivitis and periodontitis: A web-based expert system utilizing certainty factor analysis. Journal of Engineering Technology and Applied Sciences, 5(3), 106-112. https://doi.org/10.36079/lamintang.jetas-0503.337
-
Alvira, M., et al. (2024). Expert system for diagnosing dental and oral diseases using the forward chaining method. https://doi.org/10.62671/perfect.v1i1.1
-
Gunawan, A., & Islami, F. (2024). Implementing the certainty factor method in a dental disease expert system. Journal of Medical Informatics Technology, 27-32. https://doi.org/10.37034/medinftech.v2i2.33
-
Yansyah, I. R., & Sumijan, S. (2021). Sistem pakar metode forward chaining untuk mengukur keparahan penyakit gigi dan mulut. Jurnal Sistim Informasi dan Teknologi, 3, 41-47. https://doi.org/10.37034/jsisfotek.v3i2.42
-
Putri, E. M., Apriliza, T., & Putri, R. N. (2021). Sistem pakar diagnosa penyakit pada perokok dengan metode forward chaining berbasis web. Jurnal SANTI - Sistem Informasi dan Teknik Informatika, 1(1), 27-37. https://doi.org/10.58794/santi.v1i1.9
-
Wijaya, M. R. (2021). Implementasi metode forward chaining sistem pakar untuk diagnosis penyakit pada perokok. SAINTEK (Jurnal Sains dan Teknologi), 3(1), 27-30.
-
Azit, A., & Azahar, A. (2023). Sistem pakar mendiagnosis penyakit gigi expert system diagnosis dental disease. Applied Information Technology and Computer Science, 4(1), 1637-1653. https://doi.org/10.30880/aitcs.2023.04.01.099
-
Walhidayat, W., & Nanda, R. (2019). Sistem pakar diagnosa penyakit gigi menggunakan metode forward chaining (studi kasus: Klinik gigi drg. Tetra Asmira Teluk Kuantan). JURTEKSI (Jurnal Teknologi dan Sistem Informasi), 5(2), 147-152. https://doi.org/10.33330/jurteksi.v5i2.344
-
Zalmi, W. F. (2023). Sistem pakar pendeteksi penyakit gigi dan mulut dengan menggunakan metode forward chaining. Nuclear Physics, 13(1), 104-116. https://doi.org/10.36987/informatika.v11i1.3846
-
Kabu, M., Ngaga, E., & Sinlae, A. A. J. (2023). Penerapan certainty factor dalam diagnosa penyakit gigi dan mulut berbasis web di Puskesmas Halilulik. JUKI Jurnal Komputer dan Informatika, 5(1), 110-123. https://www.ioinformatic.org/index.php/JUKI/article/view/184
-
Zalukhu, A. I., Syahputra, I., & Sitorus, Z. (2023). Bulletin of information technology (BIT) penerapan metode certainty factor pada sistem pakar diagnosa penyakit gigi dan mulut. 4(4), 544-553. https://journal.fkpt.org/index.php/BIT
-
Dian, R., Sumijan, S., & Yuhandri, Y. (2020). Sistem pakar dalam identifikasi kerusakan gigi pada anak dengan menggunakan metode forward chaining dan certainty factor. Jurnal Sistim Informasi dan Teknologi, 2, 65-70. https://doi.org/10.37034/jsisfotek.v2i3.24
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