Application of Certainty Factor Methods in the Development of Expert Systems in Diagnosing Asthma

Authors

  • Sahlino Sahlino Department of Information Systems, Faculty of computer science, Universitas Dehasen Bengkulu
  • Dewi Suranti Department of Information Systems, Faculty of computer science, Universitas Dehasen Bengkulu
  • Rizka Tri Alinse Department of Information Systems, Faculty of computer science, Universitas Dehasen Bengkulu

DOI:

https://doi.org/10.37638/gatotkaca.v2i2.426

Keywords:

Certainty Factor Method, Expert System, Diagnosis, Asthma.

Abstract

Asthma occurs due to inflammation of the respiratory tract that causes sufferers to experience shortness of breath and wheezing. Asthma symptoms can appear due to the influence of infection, pollution, or allergies. Asthma is a type of disease that causes symptoms of narrowing and inflammation of the respiratory tract resulting in shortness of breath or difficulty breathing. Asthma can be caused by several things, namely dust, smoke, animal fur, cold air, physical activity, etc. Asthma is classified into 3 types, namely mild asthma, moderate asthma, and severe asthma. This expert system in diagnosing asthma is used to facilitate patient consultation, where the patient enters some of the symptoms he is experiencing and the system will diagnose these symptoms to determine whether asthma is classified as mild asthma, moderate asthma, or high grade asthma. In assisting the diagnosis, this expert system has applied Certainty Factor Method by proving a fact with a certainty value against that fact. The advantage of the CF method is that it can measure something that is certain or uncertain in decision making in disease diagnosis expert systems. Expert system in diagnosing asthma is made using Visual Basic.Net Programming Language with SQL database. With this expert system, it can help diagnose asthma suffered by patients based on the symptoms felt by the patient and provide solutions to deal with the disease suffered by a patient. Based on the tests that have been carried out, the functionality of the expert system application in diagnosing asthma is running as expected, and the application is able to display the results of the disease diagnosis from the symptoms selected by the patient.

 

References

Blazing, A., 2018. Pemrograman Windows Dengan Visual Basic .Net : Praktikum Pemrograman VB.Net. s.l.:Google Book.

Darnila, E., Mauliza & Ula, M., 2019. Aplikasi Teknologi Sistem Pakar Berbasis Fuzzy Clustering. Medan: Yayasan Kita Menulis.

Hayadi, B. H., 2018. Sistem Pakar Penyelesaian Kasus Menentukan Minat Baca, Kecenderungan, dan Karakter Siswa dengan Metode Forward Chaining. Pertama penyunt. Yogyakarta: Deepublish.

Kusumo, A. S., 2016. Administrasi SQL Server 2014. Jakarta: PT. Elex Media Komputindo.

Lasminiasih, 2016. Perancangan Sistem Informasi Kredit Mikro Mahasiswa Berbasis Web. Jurnal Sistem Informasi (JSI) Vol.8 No.1 April 2016 ISSN : 2085-1588.

Lubis, A., 2016. Basis Data Dasar Untuk Mahasiswa Ilmu Komputer. Yogyakarta: Deepublish.

Permana, R., Sovia, R., Reza, M. & Putra, H. P., 2020. Sistem Pakar Certainty Factor Dalam Mendiagnosis Indikasi Penyakit Katarak Pada Anak. Sebatik, Volume Vol. 24 No.1 ISSN 1410-3737.

Ramadhan, P. S. & Pane, U. F. S., 2018. Mengenal Metode Sistem Pakar. Ponorogo: Uwais Inspirasi Indonesia.

Ramadhan, P. S. & S.Pane, U. F., 2018. Mengenal Metode Sistem Pakar. Pertama penyunt. Ponorogo: Uwais Inspirasi Indonesia.

Setyaputri, K. E., Fadlil, A. & Sunardi, 2018. Analisis Metode Certainty Factor pada Sistem Pakar Diagnosa Penyakit THT. Jurnal Teknik Elektro, Volume Vol.10 No.1.

Widodo, A. W. & Kurnianingtyas, D., 2017. Sistem Basis Data. Malang: UB Press.

Published

2021-12-31

Issue

Section

Articles