SISTEM PAKAR DIAGNOSIS GANGGUAN DEMENSIA MENGGUNAKAN METODE CERTAINTY FACTOR

Anita Desiani; Muhammad Arya All Fajri

doi:10.23960/jitet.v14i1.8374

Authors

Anita Desiani Universitas Sriwijaya
Arya Universitas Sriwijaya

DOI:

https://doi.org/10.23960/jitet.v14i1.8374

Abstract Views: 34 File Views: 17

Keywords:

Dementia, Expert System, Certainty Factor

Abstract

Demensia merupakan gangguan kesehatan ditandai dengan penurunan daya ingat, kemampuan kognitif, dan perilaku yang mengganggu aktivitas pada kehidupan sehari-hari. Masyarakat kurang mendapatkan informasi mengenai deteksi dini demensia yang disebabkan terbatasnya fasilitas kesehatan. Diagnosis gangguan demensia dapat dilakukan menggunakan bantuan komputer dengan memanfaatkan sistem pakar. Penelitian ini bertujuan mengembangkan sistem pakar untuk diagnosis gangguan demensia menggunakan metode certainty factor. Sistem pakar digunakan karena mampu mensimulasikan penilaian dan perilaku sesuai dengan proses penalaran manusia. Metode certainty factor digunakan untuk menangani ketidakpastian dalam sistem berbasis aturan. Tahapan dari penelitian ini meliputi pengumpulan data, akuisisi pengetahuan, representasi pengetahuan, basis pengetahuan, teknik analisis, inferensi pengetahuan, dan penempatan pengetahuan. Pengujian dilakukan menggunakan beberapa data pengujian dan hasil sistem dibandingkan dengan penilaian pakar sebagai acuan pakar. Hasil perhitungan penilaian pakar menunjukkan bahwa metode certainty factor memperoleh akurasi sebesar 100%. Penelitian ini menunjukkan bahwa metode certainty factor memiliki performa yang sangat baik pada diagnosis gangguan demensia.

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References

M. A. Averbeck and H. Madersbacher, “Dementia,” in Handbook of Neurourology, L. Liao and H. Madersbacher, Eds., Singapore: Springer Nature Singapore, 2023, pp. 731–736. doi: 10.1007/978-981-99-1659-7_61.

WHO, “Dementia in Refugees and Migrants: Epidemiology, Public Health Implications and Global Responses,” WHO, Geneva, 2025.

WHO, A Blueprint for Dementia Research. Geneva, 2022. [Online]. Available: https://www.who.int/publications/i/item/9789240058248

A. Khan, “Introduction,” in Artificial Intelligence: A Guide for Everyone, A. Khan, Ed., Cham: Springer Nature Switzerland, 2024, pp. 1–10. doi: 10.1007/978-3-031-56713-1_1.

D. K. Chakrabarti and P. Mittal, “Expert System,” in Plant Disease Forecasting Systems, D. K. Chakrabarti and P. Mittal, Eds., Singapore: Springer Nature Singapore, 2023, pp. 67–82. doi: 10.1007/978-981-99-1210-0_7.

J. Chaki, “Certainty Factor and Evidential Reasoning to Handle Uncertainty in Artificial Intelligence,” in Handling Uncertainty in Artificial Intelligence, J. Chaki, Ed., Singapore: Springer Nature Singapore, 2023, pp. 37–45. doi: 10.1007/978-981-99-5333-2_4.

K.-T. Chang, A. Merghadi, A. P. Yunus, B. T. Pham, and J. Dou, “Evaluating Scale Effects of Topographic Variables in Landslide Susceptibility Models Using GIS-Based Machine Learning Techniques,” Sci. Rep., vol. 9, no. 1, p. 12296, Aug. 2019, doi: 10.1038/s41598-019-48773-2.

R. Pandey, A. K. Pandey, K. K. Joshi, and R. Rai, “Technical Review and Data Analysis of Expert System Development,” in Emerging Technologies in Data Mining and Information Security, P. Dutta, S. Chakrabarti, A. Bhattacharya, S. Dutta, and V. Piuri, Eds., Singapore: Springer Nature Singapore, 2023, pp. 703–708. doi: 10.1007/978-981-19-4193-1_68.

J. Talukdar, T. P. Singh, and B. Barman, “Rule-Based Expert Systems,” in Artificial Intelligence in Healthcare Industry, J. Talukdar, T. P. Singh, and B. Barman, Eds., Singapore: Springer Nature Singapore, 2023, pp. 145–158. doi: 10.1007/978-981-99-3157-6_8.

A. Hategan, J. A. Bourgeois, T. Cheng, and J. Young, “Common Major and Mild Neurocognitive Disorders: Alzheimer Disease, Frontotemporal, Lewy Body, and Vascular Types,” in Geriatric Psychiatry Study Guide, Cham: Springer International Publishing, 2018, pp. 203–242. doi: 10.1007/978-3-319-77128-1.

K. Dhungana, “Alzheimer’s Disease,” in Case-based Approach to Common Neurological Disorders, K. K. Oli, G. S. Shrestha, R. Ojha, P. K. Pal, S. Pandey, and B. Das, Eds., Singapore: Springer Nature Singapore, 2024, pp. 323–327. doi: 10.1007/978-981-99-8676-7_37.

M. P. E. Van Engelen et al., “Altered Brain Metabolism in Frontotemporal Dementia and Psychiatric Disorders : Involvement of The Anterior Cingulate Cortex,” EJNMMI Res., vol. 13, no. 71, pp. 1–14, 2023, doi: 10.1186/s13550-023-01020-2.

A. Badji, J. Youwakim, A. Cooper, E. Westman, and A. Marseglia, “Vascular Cognitive Impairment – Past , Present , and Future Challenges,” Ageing Res. Rev., vol. 90, no. 102042, pp. 1–16, 2023, doi: 10.1016/j.arr.2023.102042.

Y. Shang, “Expert Systems,” in The Electrical Engineering Handbook, W.-K. Chen, Ed., Burlington: Elsevier, 2005, pp. 367–377. doi: 10.1016/B978-012170960-0/50031-1.

J. E. Aronson, “Expert Systems,” in Encyclopedia of Information Systems, H. Bidgoli, Ed., New York: Elsevier, 2003, pp. 277–289. doi: 10.1016/B0-12-227240-4/00067-8.

M. K. Bergman, A Knowledge Representation Practionary. Cham: Springer International Publishing, 2018. doi: 10.1007/978-3-319-98092-8.

L. Zhang, Y. Pan, X. Wu, and M. J. Skibniewski, “Expert Systems,” in Artificial Intelligence in Production Engineering and Management, Singapore: Springer, Singapore, 2021, pp. 201–230. doi: 10.1007/978-981-16-2842-9_9.

D. Das, A. K. Kolya, S. Sarkar, and A. Basu, “Sentiment Analysis and Computational Intelligence,” in Computational Intelligence Applications for Text and Sentiment Data Analysis, D. Das, A. K. Kolya, A. Basu, and S. Sarkar, Eds., Elsevier, 2023, pp. 1–16. doi: 10.1016/B978-0-32-390535-0.00006-9.

K. Baxter, C. Courage, and K. Caine, “Field Studies,” in Understanding Your Users (Second Edition): A Practical Guide to User Research Methods Interactive Technologies, Elsevier, 2015, pp. 378–428. doi: 10.1016/B978-0-12-800232-2.00013-4.

P. Evangeline and Anandhakumar, “Digital Twin Technology for ‘Smart Manufacturing,’” in Advances in Computers, 1st ed., vol. 117, no. 1, Elsevier Inc., 2020, pp. 35–49. doi: 10.1016/bs.adcom.2019.10.009.

L. Zhang and B. Zhang, “Reasoning in Multi-Granular Worlds,” in Quotient Space Based Problem Solving, Elsevier, 2014, pp. 129–191. doi: 10.1016/B978-0-12-410387-0.00004-4.

I. Astuti, H. Sutarno, and Rasim, “The Expert System of Children’s Digestive Tract Diseases Diagnostic Using Combination of Forward Chaining and Certainty Factor Methods,” in 2017 3rd International Conference on Science in Information Technology (ICSITech), IEEE, Oct. 2017, pp. 608–612. doi: 10.1109/ICSITech.2017.8257185.

L.-H. Yang, F.-F. Ye, J. Liu, and Y.-M. Wang, “Belief Rule-Base Expert System with Multilayer Tree Structure for Complex Problems Modeling,” Expert Syst. Appl., vol. 217, p. 119567, May 2023, doi: 10.1016/j.eswa.2023.119567.