Expert System Design for Early Detection of Tuberculosis Disease (Case Study at Demak District Health Office)

Authors

  • Adinda Cipta Dewi Universitas Diponegoro
  • Kusworo Adi Universitas Diponegoro
  • Martini Martini Universitas Diponegoro

DOI:

https://doi.org/10.55927/eajmr.v3i7.9675

Keywords:

System Design, Expert System, Early Detection, Tuberculosis, Suspected

Abstract

This research aims to design an expert system for early detection of Tuberculosis (TB) disease. The existence of this system is reduce the number of TB patients in the community. The expert system concept developed is building relationships of TB symptoms based on knowledge obtained from the TB programmer at the Demak District Health Office and the form used for TB screening as a reference for knowledge in this system. Based on the results, the system is designed to be able to diagnose TB disease based on the symptoms felt by the user. It will validate rule matches based on 1 main symptom and 6 additional symptoms to get TB diagnosis results, called suspected tuberculosis or not suspected tuberculosis.

References

Bock, C., Clancey, W. J., Cuena, J., Johnson, P. E., Moen, J. B., Prade, H., Sauers, R., Shibahara, T., Tanaka, T., & Thompson, W. B. (2012). Expert System Applications. Springer Science & Business Media.

Idensia, F., Yuhandri, Y., & Hendrik, B. (2024). Penerapan Teorema Bayes Pada Sistem Pakar Untuk Mendeteksi Dini Penyakit Tuberkulosis (Studi Kasus Di Rs. Tentara Dr. Reksodiwiryo Padang). Kesatria: Jurnal Penerapan Sistem Informasi (Komputer Dan Manajemen), 5(2), 595–604.

Kemenkes. (2014). Pengendalian Penyakit dan Penyehatan Lingkungan. Pedoman Nasional Pengendalian Tuberkulosis. Jakarta: Kemenkes RI.

Kusrini. (2008). Aplikasi Sistem Pakar Menentukan Faktor Kepastian Pengguna dengan Metode Kuantifikasi Pertanyaan. Yogyakarta: Andi.

Lucas, P. J. F., & Van Der Gaag, L. C. (1991). Principles of Expert Systems. Addison Wesley Longman.

Madona, A., Pratiwi, E. C., Adi, M. A. B., Nugraha, R. P., Qinaya, Z. P., Arifah, I., Cahyanti, E. T., & Utami, H. P. (2023). Skrining Penyakit Menular Tuberculosis Pada Masyarakat di Kecamatan Kartasura Kabupaten Sukoharjo. PROSIDING SEMINAR KESEHATAN MASYARAKAT, 1(Oktober), 191–200.

Nabila, A. A. (2023). Sistem Pakar Diagnosa Penyakit Tuberkulosis Dengan Metode Certainty. Journal of Artificial Intelligence and Software Engineering, 3(1), 1–6.

RI, M. K. (2016). Permenkes Nomor 67 Tahun 2016 tentang Penanggulangan Tuberkulosis.

Ruliah, R., Aida, N., & Soegiarto, S. (2020). Rancangan Sistem Pakar Untuk Mendiagnosa Penyakit Tuberkulosis Berbasis Certainty Factor. Jutisi: Jurnal Ilmiah Teknik Informatika Dan Sistem Informasi, 9(1), 151–161.

Shih, Y.-J., Ayles, H., Lönnroth, K., Claassens, M., & Lin, H.-H. (2019). Development and Validation of A Prediction Model for Active Tuberculosis Case Finding Among HIV-Negative/Unknown Populations. Scientific Reports, 9(1), 6143.

WHO. (2022). Global Tuberculosis Report 2022.

WHO. (2023a). Tuberculosis.

WHO. (2023b). World Tuberculosis Day 2023.

Zendrato, E. L. P., Fadillah, R., & Sidiq, R. J. (2023). Tinjauan Literatur Sistematik pada Sistem Pakar untuk Diagnosa Penyakit Manusia. AI Dan SPK: Jurnal Artificial Intelligent Dan Sistem Penunjang Keputusan, 1(1), 1–8.

Ziliwu, J. B. P., & Girsang, E. (2022). The Relationship Of Knowledge And Attitudes Towards Medication Adherence In Tuberculosis Patients In Medan Pulmonary Specialty Hospital. Jambura Journal of Health Sciences and Research, 4(3), 999–1006.

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Published

2024-07-08

How to Cite

Dewi, A. C., Adi, K., & Martini, M. (2024). Expert System Design for Early Detection of Tuberculosis Disease (Case Study at Demak District Health Office). East Asian Journal of Multidisciplinary Research, 3(7), 2571–2580. https://doi.org/10.55927/eajmr.v3i7.9675

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Articles