Implementation of the Bayes theorem method for identifying diseases of children under five

Authors

  • Macro Ramadhani Universitas Labuhan Batu
  • Volvo Sihombing Universitas Labuhanbatu
  • Masrizal Masrizal Universitas Labuhan Batu

DOI:

10.33395/sinkron.v5i2.10907

Abstract

Disease is very susceptible to occur in children under five because the immune system in children under five has not been fully developed. Lack of knowledge about the diseases of children under five and the symptoms they experience makes parents fearful. The lack of knowledge of children's diseases from experts can result in delayed treatment. Problems that occur can be overcome by utilizing artificial intelligence technology. One of the artificial intelligence technologies is an expert system. Information needs very quickly from an expert to deal with problems or diseases of children under five that are expected by parents or society. So that is what drives the development of a software application, namely an expert system for the identification of diseases of children under five. An expert system for the identification of toddlers' diseases is made as a tool to diagnose diseases experienced by toddlers by using the symptoms experienced by toddlers as a tool to detect diseases experienced by children under five. The system can identify 5 types of disease with 23 symptoms of disease. This expert system uses the development method of problem identification, system design, implementation and testing. Inference in this expert system uses the Bayes theorem method. This system is built with Visual Basic and Microsoft Access as the database. The results of consulting tests with this system show that the system is able to determine the disease along with the initial treatment and treatment solutions that must be carried out, based on the symptoms previously selected by the user.

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References

Aini, N., Ramadiani, R., & Hatta, HR (2017). Expert System for Tuberculosis Diagnosis. Mulawarman Informatics: Scientific Journal of Computer Science. https://doi.org/10.30872/jim.v12i1.224

Aji, AH, Furqon, MT, & Widodo, AW (2018). Expert System for Diagnosing Pregnant Women Diseases Using the Certainty Factor (CF) Method. Journal of Information Technology and Computer Science Development, 2 (5), 2127–2134. http://j-ptiik.ub.ac.id/index.php/j-ptiik/article/view/1556

Dewi, PS, Lestari, RD, & Lestari, RT (2015). KOI FISH DISEASE DIAGNOSIS SYSTEM WITH BAYES METHOD. Komputa: Journal of Computer Science and Informatics. https://doi.org/10.34010/komputa.v4i1.2404

Fricles Ariwisanto Sianturi. (2019). Bayes theorem analysis method in diagnosing miscarriage in pregnant women based on type of food Information and Computer Engineering (Tekinkom), 2 (1), 87–92. http://jurnal.murnisadar.ac.id/index.php/Tekinkom/article/view/78

Gunawan, EP, & Wardoyo, R. (2018). An Expert System Using Certainty Factor for Determining Insomnia Acupoint. IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 12 (2), 119. https://doi.org/10.22146/ijccs.26328

Harijanto, B., & Latif, RA (2016). DISEASE DIAGNOSIS EXPERT SYSTEM IN CATS USING ANDROID BASED BAYES THEOREME METHOD. Journal of Polinema Informatics. https://doi.org/10.33795/jip.v2i4.79

Murni, S., & Riandari, F. (2018). Application of the Bayes Theorem Method to the Expert System to Diagnose Gastric Disease. Prima Journal of Technology and Computer Science (JUTIKOMP). https://doi.org/10.34012/jutikomp.v1i2.226

Muslim, AA et al. (2015). Expert System for Diagnosis of Pests and Diseases of Chili Based on Bayes Theorem. Millionaire.

Pramudia, H., & Nugroho, A. (2017). Laptop Damage Information System Using Naïve Bayes Method. Electrical Technology, Mercu Buana University.

Ramadhan, PS (2018). Expert System for Diagnosing Immune Dermatitis Using Bayes Theorem. InfoTekJar (National Journal of Informatics and Network Technology). https://doi.org/10.30743/infotekjar.v3i1.643

Ramadan, PS (2019). Application of Comparison of Bayes' Theorem with Euclidean Probability in Dermatic Bacterial Diagnosis. InfoTekJar (National Journal of Informatics and Network Technology). https://doi.org/10.30743/infotekjar.v4i1.1579

Ramadan, PS, & Pane, UFS (2018). Comparative Analysis of Methods (Certainty Factor, Dempster Shafer and Bayes Theorem) to Diagnose Inflammatory Dermatitis in Children. SAINTIKOM Journal (Journal of Information Management and Computer Science).

Sasangka, B., & Witanti, A. (2019). Expert System for Diagnosing Acute Respiratory Infectious Diseases in Children Using Bayes's Theorem. JMAI (Journal of Multimedia & Artificial Intelligence). https://doi.org/10.26486/jmai.v3i2.83

Sianturi, FA (2019). Implementation of the Certainty Factor Method for Diagnosing Computer Damage. MEANS (Media Information Analysis and Systems), 4 (2), 176–184.

Sinaga, B., Hasugian, PM, & Manurung, AM (2018). Expert System to Diagnose Smartphone Damage. 3 (1), 333–339.

Syahputra, T., Dahria, M., & Putri, PD (2017). Expert System To Diagnose Anemia Using Bayes Theorem Method. SAINTIKOM Journal.

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How to Cite

Ramadhani, M., Sihombing, V. ., & Masrizal, M. (2021). Implementation of the Bayes theorem method for identifying diseases of children under five. Sinkron : Jurnal Dan Penelitian Teknik Informatika, 5(2), 260-265. https://doi.org/10.33395/sinkron.v5i2.10907

Issue

Vol. 5 No. 2 (2021): Article Research Volume 5 Number 2, April 2021

Section

Articles

License

Copyright (c) 2021 Macro Ramadhani, Volvo Sihombing, Masrizal

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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