DOI of the published article https://doi.org/10.36040/jati.v10i1.16919
An Expert System for Early Detection of Stroke Using a Web-Based Hybrid Method
Sistem Pakar Deteksi Dini Penyakit Stroke Menggunakan Metode Hybrid Berbasis Web
DOI:
https://doi.org/10.21070/ups.10026Keywords:
Expert System, Stroke, Forward Chaining, Certainly Factor, Early Detection, Web-Based ApplicationAbstract
Stroke is a serious disease that can cause death and permanent disability if not treated promptly. This study develops a web-based expert system for early stroke detection using a hybrid Forward Chaining and Certainty Factor method. Forward Chaining is applied to process diagnostic rules based on user-selected symptoms, while Certainty Factor determines the confidence level of the diagnosis. The system is built using JavaScript and MySQL, providing data management for admins and diagnostic services for users. Black Box testing shows that all system features function properly, and user testing indicates the system is easy to use and presents clear information. This system is expected to support early recognition of stroke symptoms and assist initial decision-making.
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References
R. S. N. H. S. E. Hutama, “Sistem Pakar Deteksi Dini Penyakit Stroke Menggunakan Metode Dempster Shafer,” vol. 10, no. 1, pp. 1–10, 2021.
S. S. Mayang and A. Eviyanti, “Expert System for Diagnosing Early Symptoms of Stroke Using the Fuzzy Mamdani Method Sistem Pakar Diagnosa Gejala Dini Penyakit Stroke Menggunakan Metode Fuzzy Mamdani,” vol. 1, no. 2, 2021.
J. Handoyo and A. Meydiana, “Aplikasi Sistem Pakar Untuk Mendiagnosis Penyakit Stroke Menggunakan Metode Forward Chaining Berbasis Web,” J. SITECH Sist. Inf. dan Teknol., vol. 5, no. 2, pp. 105–112, 2023, doi: 10.24176/sitech.v5i2.9240.
S. Moon, Y. S. Yang, H. Kimm, K. J. Jung, J. Y. Lee, and S. H. Jee, “Do Weight Changes Affect the Association between Smoking Cessation and the Risk of Stroke Subtypes in Korean Males ?,” 2023.
F. Lezzar, S. E. Mili, and M. Constantine, “Deep Learning for Stroke Classification Using Multi-Slice CT Image Analysis,” vol. 7, no. 3, pp. 850–868, 2025.
M. K. Husen, D. Triyanti, D. Prania, and D. M. Efendi, “EXPERT SYSTEM FOR DIAGNOSING PERSONALITY DISORDERS USING FORWARD CHAINING AND,” vol. 5, no. 12, 2024.
N. Yasmin, Y. Yuhandri, and G. W. Nurcahyo, “BULLETIN OF COMPUTER SCIENCE RESEARCH Analisis Metode Forward Chaining dan Certainty Factor untuk Diagnosa Penyakit pada Ibu Hamil,” vol. 5, no. 5, pp. 1195–1202, 2025, doi: 10.47065/bulletincsr.v5i5.756.
R. Diana and R. R. Fiska, “Metode Forward Chaining untuk Diagnosa dan Penanganan Penyakit Stroke dengan Sistem Pakar,” vol. 2, no. 5, pp. 338–350, 2024.
S. Matondang, “Sistem Pakar Diagnosis Penyakit Umum Menggunakan Metode Forward Chaining,” vol. 7, pp. 1712–1723, 2023.
A. P. Nugraha, Ayu Oktavia; Voutama, “Penerapan Metode Certainty Factor Dan Forward Chaining Pada Sistem Pakar Berbasis Web Dalam Mendiagnosis Penyakit Lambung,” vol. 10, no. 1, pp. 140–175, 2024.
H. Soetanto and M. K. Suryadewiansyah, “Optimization of Expert System Based on Interpolation , Forward Chaining , and Certainty Factor for Diagnosing Abdominal Colic,” 2024, doi: 10.3844/jcssp.2024.191.197.
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