Expert System for Diagnosing Chicken Diseases using Bayes' Theorem
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Abstract
Chicken disease is a condition in which the organs of the chicken farm cannot function normally. To make a diagnosis of the disease requires further examination carried out by specialists (experts). An expert system is a system that uses human knowledge entered into a computer to solve problems that are usually solved by experts. The system created in solving the problem uses the Bayes theorem method where the inference process uses Forward Chaining. The application was developed using the Visual Basic 2010 programming language and MySQL database.
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How to Cite
Simatupang, M. A. B. (2020). Expert System for Diagnosing Chicken Diseases using Bayes’ Theorem. International Journal of Basic and Applied Science, 9(1), 20–28. https://doi.org/10.35335/ijobas.v9i1.10
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M. Tekege, “Pemanfaatan teknologi informasi dan komunikasi dalam pembelajaran SMA YPPGI Nabire,” J. FATEKSA J. Teknol. Dan Rekayasa, vol. 2, no. 1, 2017.
J. C. Giarratano and G. D. Riley, Expert systems: principles and programming. Brooks/Cole Publishing Co., 2005.
S. N. D. Abdurohman, Dunia Burung dan Serangga: Mengenal Fakta Sains dan Keunikannya. Zikrul Hakim Bestari, 2014.
H. T. Sihotang, F. Riandari, R. M. Simanjorang, A. Simangunsong, and P. S. Hasugian, “Expert System for Diagnosis Chicken Disease using Bayes Theorem,” in Journal of Physics: Conference Series, 2019, vol. 1230, no. 1, p. 12066.
I. W. Priyana, D. H. Satyareni, and E. N. Jannah, “Rancang Bangun Sistem Pakar Diagnosis Penyakit Mata Dengan Metode Teorema Bayes,” Edutic-Sci. J. Informatics Educ, vol. 2, no. 1, pp. 1–7, 2016.
M. R. Fadhillah, I. Ishak, and P. S. Ramadhan, “IMPLEMENTASI SISTEM PAKAR MENDIAGNOSA PENYAKIT PENYAKIT GASTRITIS DENGAN MENGGUNAKAN METODE TEOREMA BAYES,” J-SISKO TECH (Jurnal Teknol. Sist. Inf. dan Sist. Komput. TGD), vol. 4, no. 1, pp. 1–9, 2021.
D. Nofriansyah, R. Gunawan, and E. Elfitriani, “Sistem Pakar Untuk Mendiagnosa Penyakit Pertussis (Batuk Rejan) Dengan Menggunakan Metode Teorema Bayes,” J-SISKO TECH (Jurnal Teknol. Sist. Inf. dan Sist. Komput. TGD), vol. 3, no. 1, pp. 41–54, 2020.
A. M. Ellison, “An introduction to Bayesian inference for ecological research and environmental decision‐making,” Ecol. Appl., vol. 6, no. 4, pp. 1036–1046, 1996.
F. Taroni, A. Biedermann, S. Bozza, P. Garbolino, and C. Aitken, Bayesian networks for probabilistic inference and decision analysis in forensic science. John Wiley & Sons, 2014.
S. R. Watson, “The meaning of probability in probabilistic safety analysis,” Reliab. Eng. Syst. Saf., vol. 45, no. 3, pp. 261–269, 1994.
A. Rido’i and R. Wardhani, “Sistem Pakar Mendiagnosa Penyakit Pada Unggas Dengan Metode Teorema Bayes Berbasis Web,” Joutica, vol. 2, no. 2, 2017.
A. A. Muslim, R. Arnie, and S. Sushermanto, “Sistem Pakar Diagnosa Hama Dan Penyakit Cabai Berbasis Teorema Bayes,” Jutisi J. Ilm. Tek. Inform. dan Sist. Inf., vol. 4, no. 3, 2016.
H. Listiyono, “Merancang dan Membuat Sistem Pakar,” Dinamik, vol. 13, no. 2, 2008.
R. Z. Rahman and T. N. Padilah, “SISTEM PAKAR HAMA DAN PENYAKIT CABAI BERBASIS TEOREMA BAYES (STUDI KASUS: DINAS PERTANIAN KARAWANG),” JUTEKIN (Jurnal Tek. Inform., vol. 9, no. 1, 2021.
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