Expert System for Diagnosing Respiratory Diseases Using the Forward Chaining Method
DOI:
https://doi.org/10.65371/metrokom.v2i1.97Keywords:
Expert System, Respiratory Diseases, Forward Chaining, Diagnosis, Artificial IntelligenceAbstract
Respiratory diseases are one of the health disorders whose prevalence continues to increase and require rapid and accurate diagnosis to support effective medical treatment. This study aims to develop an expert system for diagnosing respiratory diseases using the forward chaining method. This method was chosen for its ability to perform data-driven reasoning, starting from the facts of the symptoms experienced by the patient, which then trigger certain rules to produce a diagnostic conclusion. The system is designed with a knowledge base containing validated data on symptoms and types of respiratory diseases, as well as an inference engine to process diagnostic rules. The system is implemented using a web-based programming language with database integration that stores information on symptoms, diseases, and reasoning rules. Test results show that the system is capable of providing quick and accurate initial diagnoses based on the symptom data entered, and can serve as a tool for medical professionals and the public in detecting respiratory diseases early. This research is expected to contribute to the development of artificial intelligence-based health technology that supports more effective and efficient medical services.
References
Anggara, Y. A. R., Wibowo, S. A., & Pranoto, Y. A. (2025). Sistem Pakar Diagnosa Kerusakan Laptop Berbasis Forward Chaining Dan Certainty Factor. IJAI (Indonesian Journal of Applied Informatics), 9(2), 296–309. https://doi.org/https://doi.org/10.20961/ijai.v9i2.95556
Ashar, S. F., & Iqbal, F. (2024). Web-Based Information System for Borrowing Practical Laboratory Equipment for The Faculty of Public Health. Jurnal Metrokom: Media Teknik Elektro Dan Komputer, 1(2), 121–133. https://doi.org/https://doi.org/10.1307/metrokom.v1i2.77
Elkana, S. R., & Kuswanto, V. (2023). Analysis and Design of Disease Diagnosis Systems and Patient Medicine Recommendations with Forward Chaining Method. Bit-Tech, 6(2), 134–143. https://doi.org/https://doi.org/10.32877/bt.v6i2.937
Mardian, D. R., Risnanto, S., Garnia, E., Adhinugraha, K. M., Rahayu, H., & Rachman, R. S. (2023). Forward Chaining and Certainly Factor Method Optimization for Lung Disease Expert System. 2023 17th International Conference on Telecommunication Systems, Services, and Applications (TSSA), 1–4. https://doi.org/10.1109/TSSA59948.2023.10366958
Mauliza, M., Ula, M., Saputra, I., Afdelina, R., & Ikhsan, M. (2022). Application of expert system with forward chaining method in detecting infectious diseases in children. Science Midwifery, 10(4), 2777–2785. https://doi.org/https://doi.org/10.35335/midwifery.v10i4.714
Nengsih, Y., & Putra, N. (2020). SISTEM PAKAR MENGGUNAKAN FORWARD CHAINING DAN CERTAINTY FACTOR UNTUK DIAGNOSA KERUSAKAN SMARTPHONE. JURSIMA, 8(2), 61–69. https://doi.org/10.47024/js.v8i2.205
Nugroho, A., & Rahmadani, N. F. (2024). Web-based Visit List Information System at the Ministry of Religious Affairs of Deli Serdang Regency. Jurnal Metrokom: Media Teknik Elektro Dan Komputer, 1(2), 58–74. https://doi.org/https://doi.org/10.1307/metrokom.v1i2.79
Putra, H., Harahap, I. S., Islam, U., & Sumatera, N. (2024). Expert System for Detecting Potential Obesity in the Environment of the State Islamic University of North Sumatra Using Naïve Bayes Classifier. Jurnal Media Teknik Elektro Dan Komputer, 1(1), 27–36.
Rifki, M. I., Raditya, M. E., & Hasugian, A. H. (2023). Text Data Security Application Using a Mobile-Based Base64 Algorithm. Instal: Jurnal Komputer, 15(02), 224–235. https://doi.org/https://doi.org/10.54209/jurnalkomputer.v15i02.146
Rifki, M. I., & Syamia, N. (2024). Message Security Application Using Mobile-Based AES Algorithm. Journal of Computer Science, Information Technology and Telecommunication Engineering, 5(2), 595–606. https://doi.org/https://doi.org/10.30596/jcositte.v5i2.20834
Sinaga, Y. A., & Aida, M. (2025). WEB-BASED EMPLOYEE LEAVE APPLICATION SYSTEM AT THE DINAS PENANAMAN MODAL DAN PELAYANAN TERPADU SATU PINTU KOTA MEDAN. Jurnal Metrokom: Media Teknik Elektro Dan Komputer, 2(1), 1–17. https://doi.org/https://doi.org/10.1307/metrokom.v2i1.100
Sukma, I., & Petrus, M. (2020). Sistem Pakar Penyakit Kucing Menggunakan Metode Forward Chaining Berbasis Web. Simtek: Jurnal Sistem Informasi Dan Teknik Komputer, 5(1), 52–58. https://doi.org/https://doi.org/10.51876/simtek.v5i1.73
Syamsudin, I., & Sudarsono, E. (2022). Penerapan Metode Certainty Factor Pada Sistem Pakar Mendiagnosa Penyakit Tuberculosis (Tb) Paru Berbasis Web Mobile. JUSIM (Jurnal Sistem Informasi Musirawas), 7(2), 127–136. https://doi.org/doi.org/ 10.35970/ jinita.v5i2.2096
Wajidi, F., & Nur, N. (2021). Sistem Pakar Diagnosis Penyakit Stunting pada Balita menggunakan Metode Forward Chaining. Jurnal Informatika Universitas Pamulang, 6(2), 401–407. https://doi.org/DOI: 10.32493/informatika.v6i2.11938
Ware, S., Yue, C., Morillo, R., Lu, J., Shang, C., Bi, J., Kamath, J., Russell, A., Bamis, A., & Wang, B. (2020). Predicting depressive symptoms using smartphone data. Smart Health, 15, 100093. https://doi.org/https://doi.org/10.1016/j.smhl.2019.100093
Wenda, A., Kraugusteeliana, K., Suryanto, A. A., Suhada;, & Karya;, S. N. A. (2023). Sistem Pakar Untuk Mendiagnosa Penyakit Paru-Paru dengan Menggunakan Metode Teorema Bayes. Jurnal Media Informatika Budidarma, 7(1). https://doi.org/https://doi.org/10.30865/mib.v7i1.5394
