Implementation of Naïve Bayes Method Diagnosing Diseases Nile Tilapia

Ridho Wahyudi Pulungan; Sriani Sriani; Armansyah Armansyah

doi:10.47709/cnahpc.v6i2.3834

Authors

Ridho Wahyudi Pulungan Universitas Islam Negeri Sumatera Utara
Sriani Universitas Islam Negeri Sumatera Utara
Armansyah Universitas Islam Negeri Sumatera Utara

DOI:

10.47709/cnahpc.v6i2.3834

Keywords:

Aquaculture, Expert System, Naïve Bayes, Nile Tilapia, Nile Tilapia Farmers

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Abstract

The Nile tilapia, also known as Oreochromis niloticus, was a freshwater fish species first produced in East Africa in 1969. It became a popular aquaculture fish in freshwater ponds across Indonesia. Besides its delicious taste, the Nile tilapia is rich in nutrients essential for human health. However, cultivating Nile tilapia was challenging due to frequent bacterial diseases. These diseases often led to mass fish deaths, causing financial losses, especially for new fish farmers. The rapid spread of diseases emphasized the need for prompt intervention to prevent further losses. Farmers needed adequate knowledge about Nile tilapia diseases, but often struggled to absorb information provided by the government. Hence, the presence of experts or veterinarians was crucial in assisting farmers to address these issues. Farmers of Nile tilapia sought assistance from experts or veterinarians, but this was not easy. It involved substantial costs and time, while quick intervention was necessary to mitigate losses. The solution proposed was the development of an expert system for diagnosing and treating Nile tilapia diseases. Thus, an expert system was built to assist fish farmers in identifying fish diseases and their treatments by implementing the naïve Bayes method. The expert system transferred human knowledge to computers, enabling them to solve problems like experts, thereby making expert knowledge accessible to non-experts. Naïve Bayes was implemented to determine the highest probability based on input symptoms. This research used five test data samples to apply the naïve Bayes method to diagnose Nile tilapia diseases, resulting in an accuracy rate of 80%. Therefore, the implementation of naïve Bayes in diagnosing Nile tilapia diseases is considered reasonably effective.

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References

Alam, P. S., Wantoro, A., & Kisworo. (2022). SISTEM PAKAR PEMILIHAN SAMPO PRIA DENGAN MENGGUNAKAN METODE CERTAINTY FACTOR. Jurnal Teknologi Dan Sistem Informasi (JTSI), 3(4), 21–27.

Anggi, Tania Anjelita Pasaribu, Hutabarat, N., & Kurniawan, A. (2023). SOSIALISASI PEMANFAATAN HERBAL DALAM MENANGGULANGI PENYAKIT PADA BUDIDAYA IKAN NILA DI TILAPIA FISH FARM, RIDING PANJANG. Jurnal GEMBIRA (Pengabdian Kepada Masyarakat), 1(5), 1140–1146.

Anwar, M. A. U., Subroto, I. M. I., & Taufik, M. (2022). Sistem Pakar Diagnosa Penyakit Ikan Nila Berbasis Metode Bayes. Jurnal Transistor Elektro Dan Informatika (TRANSISTOR EI), 4(1), 1–10.

Arsatria, T., Munadi, K., & Arnia, F. (2020). Pengolahan Citra Termal untuk Identifikasi Region of Interest (ROI) dan Deteksi Kesegaran Ikan Nila (Oreochromis niloticus). KITEKTRO: Jurnal Online Teknik Elektro, 5(3), 20–24.

Azhar, F., Junaidi, M., Muklis, A., & Scabra, A. R. (2020). ENANGGULANGAN PENYAKIT MAS (MOTILE AEROMONAS SEPTICEMIA) PADA IKAN NILA MENGGUNAKAN EKSTRAK TEMULAWAK (CURCUMA XANTHORRIZA ROXB). Jurnal Abdi Insani Universitas Mataram, 7(3), 320–324.

Batubara, M. Z., & Nasution, M. I. P. (2023). Sistem Informasi Online Pengelolaan Dana Sosial Pada Rumah Yatim Sumatera Utara. Jurnal Teknologi Dan Sistem Informasi Bisnis, 5(3), 164–171.

Nugraha, E. H., Elinah, Ekawati, N., & Maulana, T. (2023). UPAYA MENINGKATKAN PRODUKTIVITAS PEMBENIHAN IKAN NILA NIRWANA (Oreochromis niloticus) DI UPTD BENIH IKAN DUKUPUNTANG KABUPATEN CIREBON, JAWA BARAT. ASWAJA, 4(1), 37–46.

Saripurna, D., & Syahputra, T. (2020). Perancangan Sistem Pakar Mendiagnosa Penyakit Bakteri Pada Ikan Lele Di Dinas Kelautan Dan Perikanan Serdang Begadai Menggunakan Metode Dempster Shafer. Cyber Tech, 10(10), 1–11.

Sianturi, F. A. (2019). ANALISA METODE TEOREMA BAYES DALAM MENDIAGNOSA KEGUGURAN PADA IBU HAMIL BERDASARKAN JENIS MAKANAN. Jurnal TEKINKOM, 2(1), 87–92.

Sianturi, I. T., Lestari, S., & Nalle, M. M. . (2021). Pengamatan Ektoparasit Pada Ikan Nila di Balai Pengembangan Teknologi Perikanan Budidaya DIY, Argomulyo, Cangkringan, Sleman. JVIP, 2(1), 11–13.

Sinubu, W. V., Tumbol, R. A., Undap, S. L., Manoppo, H., & Kreckhoff, R. L. (2022). Identifikasi bakteri patogen Aeromonas sp. pada ikan Nila (Oreochromis niloticus) di Desa Matungkas, Kecamatan Dimembe, Kabupaten Minahasa Utara. Budidaya Perairan, 10(2), 109–120.

Suherman, B. B. (2021). SISTEM PAKAR DIAGNOSA PENYAKIT DAN HAMA PADA TANAMAN JAGUNG MENGGUNAKAN METODE NAIVE BAYES. Jurnal Informatika Dan Rekayasa Perangkat Lunak (JATIKA), 2(3), 390–398.

Syahranitazli, & Samsudin. (2023). SISTEM INFORMASI GEOGRAFIS PERSEBARAN PONDOK PESANTREN KABUPATEN LANGKAT DAN BINJAI MENGGUNAKAN LEAFLET. Jurnal Pendidikan Teknologi Informasi (JUKANTI), 6(1), 2621–1467.

Untari, D. S., Wibowo, T. A., & Anwar, R. (2022). Minat Konsumen Millenial Terhadap Konsumsi Ikan Air Laut dan Ikan Air Tawar. Jurnal FishtecH, 11(1), 30–38.

Utomo, H. P., Fitri, I., & Winarsih. (2020). Expert System of Diagnosis of Human Dental Diseases Using The Naïve Bayes Method. Jurnal Mantik, 3(4), 373–382.

Wibowo, T. A., & Untari, D. S. (2023). POTENSI BUAH MANGROVE (Bruguiera gymnorrhiza) DAN IKAN TEMBAKUL (Boleophthalmus pectinirostris) SEBAGAI BAHAN ALTERNATIF PEMBUATAN KAKI NAGA IKAN. Jurnal Ilmu Perikanan Dan Kelautan, 5(1), 30–45.

Yuga, D. … Fathinah, N. A. (2023). Pengembangan Pakan Ikan Berprotein Tinggi Dari Keong Mas (Pomacea Canaliculata) Terhadap Ikan Nila (Oreochromis Niloticus) Dan Penerapannya Dalam Program Kerja Kuliah Kerja Nyata Di Masyarakat Desa Sungai Petai. Kegiatan Positif: Jurnal Hasil Karya Pengabdian Masyarakat, 1(3), 93–98.