Expert System for Diagnosing Gourami Fish Diseases Using the Certainty Factor Approach
DOI:
https://doi.org/10.30595/juita.v13i1.26031Keywords:
certainty factor, disease, expert system, gourami, symptoms.Abstract
Gourami is an economically significant fish in the aquaculture sector due to its high market demand and relatively stable price. However, it is also challenging to cultivate, with disease outbreaks being one of the primary difficulties. Early diagnosis of gourami fish diseases requires expertise from fish health specialists, who are often difficult to find due to their limited availability. With advancements in artificial intelligence-based technology, this study developed an expert system to diagnose gourami fish diseases based on observed symptoms. The system employs the Certainty Factor (CF) approach to estimate the likelihood of a particular disease affecting the fish. The Certainty Factor approach utilizes a knowledge base derived from expert knowledge to address uncertainty in diagnosis. The certainty factor weights are determined based on confidence levels from both experts and users to generate an accurate diagnosis. This expert system was developed using data from 20 types of gourami fish diseases and 38 associated symptoms. The system successfully identified diseases with a certain level of confidence and provided appropriate treatment recommendations based on the confidence level obtained. By implementing this expert system, the risk of disease outbreaks can be minimized, thereby improving efficiency and productivity in gourami fish farming while helping maintain fish health and reducing economic losses caused by disease.References
[1] A. S. Ma’arif, Cara sukses budidaya ikan gurami. Penerbit Bio Genesis, 2017.
[2] A. Wantoro, H. Sulistiyani, Y. Yuniarthe, A. Setya Putra, A. Candra Widyawati, and N. Putra Wicaksono, ‘Sistem Pakar Diagnosis Penyakit Kutu Ikan Gurami (Argunus Indicus) Menggunakan Metode Naive Bayes 1’, 2022.
[3] M. Y. Nesi, Y. R. Kaesmetan, and M. O. Meo, ‘Sistem Pakar Diagnosa Penyakit Ikan Gurame Dengan Menggunakan FIS Mamdani’, HOAQ (High Education of Organization Archive Quality): Jurnal Teknologi Informasi, vol. 11, no. 2, pp. 73–80, 2020.
[4] P. Lestari, ‘Sistem Pakar Diagnosa Penyakit Ikan Nila pada Dinas Perikanan Teluk Kuantan’, JURNAL PERENCANAAN, SAINS DAN TEKNOLOGI (JUPERSATEK), vol. 2, no. 1, pp. 144–150, 2019.
[5] H. N. Suhardjito, ‘SISTEM PAKAR PENYAKIT IKAN GURAME PADA PEMBUDIDAYAAN MENGUNAKAN METODE FORWARD CHAINING’, JATI (Jurnal Mahasiswa Teknik Informatika), vol. 3, no. 1, pp. 123–128, 2019.
[6] S. Rahmaningsih, Hama & Penyakit Ikan. Yogyakarta: Deepublish, 2018.
[7] M. E. Auer, D. Guralnick, and I. Simonics, Teaching and Learning in a Digital World: Proceedings of the 20th International Conference on Interactive Collaborative Learning – Volume 2. Switzerland: Springer International Publishing, 2018.
[8] A. D. Syafaati, ‘Revolusi Industri dari Generasi 1.0 hingga 4.0’, https://www.academia.edu/37491240/REVOLUSI_INDUSTRI_DARI_GENERASI_1.0_HINGGA_4.0. Accessed: Feb. 19, 2019. [Online].
[9] B. H. Hayadi, Sistem pakar. Yogyakarta: Deepublish, 2018.
[10] H. Mustafidah and S. Suwarsito, ‘Penyusunan Formula Pakan dengan Metode Komputasi’, Purwokerto, 2004.
[11] H. Mustafidah and S. Suwarsito, ‘Sistem Pakar Sebagai Penasehat Cara Mendiagnosa Penyakit Ikan’, SAINS AKUATIK, vol. 11, no. 2, pp. 209 – 218, 2008.
[12] S. Suwarsito and H. Mustafidah, ‘Diagnosa Penyakit Ikan Menggunakan Sistem Pakar (Diagnosis of Fish Diseases Using Expert Systems)’, JUITA (Jurnal Informatika), vol. I, no. 4, pp. 123 – 131, 2011.
[13] S. Suwarsito and H. Mustafidah, ‘Determination of Appropriate Fish Culture Method Based on Water Quality Using Expert System’, Adv Sci Lett, vol. 24, no. 12, pp. 9178–9181, 2018.
[14] P. S. Ramadhan and U. F. S. S. Pane, ‘Analisis Perbandingan Metode (Certainty Factor, Dempster Shafer dan Teorema Bayes) untuk Mendiagnosa Penyakit Inflamasi Dermatitis Imun pada Anak’, Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer), vol. 17, no. 2, pp. 151–157, 2018.
[15] U. Khaira, B. Aulia, and D. Musfiroh, ‘Sistem Pakar Rekomendasi Tanaman Herbal Berdasarkan Faktor Lingkungan Menggunakan Metode Certainty Factor’, SATIN-Sains dan Teknologi Informasi, vol. 8, no. 2, pp. 101–111, 2022.
[16] S. R. Puji and F. S. P. Usti, ‘Analisis Perbandingan Metode (Certainty Factor, Dempster Shafer dan Teorema Bayes ) untuk Mendiagnosa Penyakit Inflamasi Dermatitis Imun pada Anak’, Jurnal Sains dan Komputer (SAINTIKOM), vol. 17, no. 2, pp. 151–157, 2018.
[17] R. Ginting, M. Zarlis, and R. Rosnelly, ‘Analisis Perbandingan Metode Certainty Factor dan Teorema Bayes untuk Mendiagnosa Penyakit Autis Pada Anak’, JURNAL MEDIA INFORMATIKA BUDIDARMA, vol. 5, no. 2, pp. 583–589, Apr. 2021, doi: 10.30865/mib.v5i2.2930.
[18] R. A. D. Yunas, A. Triayudi, and I. D. Sholihati, ‘Implementasi Sistem Pakar untuk Mendeteksi Virus Covid-19 dengan Perbandingan Metode Naïve Bayes dan Certainty Factor’, Jurnal Teknologi Informasi dan Komunikasi), vol. 5, no. 3, pp. 338–345, 2021, doi: 10.35870/jti.
[19] N. D. Wirasbawa, C. T. P. Widjaja, C. I. Wenji, and S. Hansun, ‘Expert API for Early Detection of TB Disease with Forward Chaining and Certainty Factor Algorithms’, Informatica (Slovenia), vol. 46, no. 6, pp. 117–124, 2022, doi: 10.31449/inf.v46i6.3947.
[20] Sumiati, H. Saragih, T. K. A. Rahman, and A. Triayudi, ‘Expert system for heart disease based on electrocardiogram data using certainty factor with multiple rule’, IAES International Journal of Artificial Intelligence, vol. 10, no. 1, pp. 43–50, 2021, doi: 10.11591/ijai.v10.i1.pp43-50.
[21] D. Heckerman, ‘Probabilistic interpretations for MYCIN’s certainty factors’, arXiv preprint arXiv:1304.3419, 2013.
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JUITA: Jurnal Informatika is licensed under a Creative Commons Attribution 4.0 International License.
