BROILER QUALITY CLASSIFICATION EXPERT SYSTEM USING THE NAÏVE BAYES METHOD
Keywords:
Expert system, Naïve Bayes, Classification, Broiler chicken, WebsiteAbstract
The quality of broilers is one of the important factors that determine the economic value and productivity of the farm. The determination of chicken quality at Pasongsongan Farm is still carried out manually based on the experience of farmers, so the assessment results are often subjective, less consistent, and take a relatively long time. This research aims to develop a web-based expert system that is able to classify the quality of broilers using the Naïve Bayes method so that the assessment process can be carried out more quickly, objectively, and computerized. The parameters used include body weight, chicken age, health condition, chicken activity, and feed consumption. Numerical data in the form of body weight and age were processed using Gaussian distribution, while categorical data in the form of health, activity, and feed consumption were calculated using a discrete probability approach with Laplace Smoothing. The system was developed using the PHP programming language with a MySQL database. The test was carried out using 150 training data and 50 test data obtained from Pasongsongan Farm. The results showed that the system was able to classify broiler quality with an accuracy rate of 78.00%, precision of 77.98%, recall of 78.00%, and F1-Score of 77.45%. These results show that the Naïve Bayes method can be applied as a method of classification of broiler quality and can help farmers in obtaining more objective and efficient assessment results
Downloads
References
Mudjiono, S. Z., Sanjaya, A., & Pamungkas, D. P. (2022). SISTEM PENDUKUNG KEPUTUSAN PENENTUAN AYAM BROILER BERKUALITAS MENGGUNAKAN METODE WP BERBASIS WEB(Doctoral dissertation, Universitas Nusantara PGRI Kediri).
Mudjiono, S. Z., Sanjaya, A., & Pamungkas, D. P. (2022, August). Sistem Pendukung Keputusan Pemilihan Ayam Broiler Berkualitas Menggunakan Metode WP. In Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) (Vol. 6, No. 1, pp. 326-331).
Fadlilah, M. A., Pauziah, U., & Ramdhan, V. (2024). Sistem Pendukung Keputusan Metode SAW Pemilihan Kualitas Telur Ayam Ras pada Agen Telor 24. Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI), 5(03), 646-655.
Febriyana, A., Hidayat, C. R., & Supriatman, A. (2024). SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN SUPLIER AYAM POTONG TERBAIK CV. TUNGGAL SADULUR MENGGUNAKAN METODE SIMPLE ADDITIVE WEIGHTING (SAW).
Tri, S. J., Nasrullah, N., Herlinah, H., & Purmatasari, D. (2021). Perbandingan Metode Weighted Product dan ELECTRE pada Sistem Pendukung Keputusan Pemilihan Pakan Ayam Broiler. JURNAL IT, 12(1), 23-29.
Abrar, A. F. (2024). SISTEM PENDUKUNG KEPUTUSAN PENENTUAN KUALITAS AYAM BROILER MENGGUNAKAN METODE SIMPLE ADDITIVE WEIGHTHING BERBASIS WEB (STUDI KASUS: PT. ARSALY JAYA SENTOSA) (Doctoral dissertation, Universitas Putra Indonesia YPTK Padang).
Fadillah, M. M., Fitriani, I., & El Farabi, M. N. (2025). Sistem Pendukung Keputusan Menentukan Kualitas Bibit Ayam Menggunakan Metode Simple Additive Weighting. Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI), 6(03), 628-637.
Waruwu, N. B., Suherdi, D., & Kusnasari, S. (2021). Sistem Pendukung Keputusan Seleksi Supplier Pemilihan Bibit Ayam Broiler Terbaik Pada CV. Berkah Jaya Abadi Menggunakan Metode Analytical Hierarchy Process(AHP). Jurnal Cyber Tech, 4(7).
Purmatasari, D., Nasrullah, N., Herlinah, H., & Jura, S. (2021). PERBANDINGAN METODE WEIGHTED PRODUCT DAN ELECTRE PADA SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN PAKAN AYAM BROILER. Jurnal IT, 12(1), 19-25.
Patappari, A., Aksa, A. N., & Herdiansyah, H. (2024). Sistem Pendukung Keputusan Identifikasi Penyakit Ayam Broiler Menggunakan Metode Saw Di Kabupaten Soppeng. Jurnal RISTER: Riset Sistem Cerdas, 1(2), 48-55.
Suryana, O. (2018). Server dan Web Server. ResearchGate, 10, 14–23.
Studi, P., Informatika, T., Teknik, F., & Janabadra, U. (2016). EVALUASI PENGGUNAAN WEBSITE UNIVERSITAS JANABADRA DENGAN. 1(1), 34–43.
Sri Hartati. (2020). Perancangan Sistem Informasi Inventaris Barang Pada Kantor Notaris Dan Ppat Ra Lia Kholila, Sh Menggunakan Visual Studio Code. Siskomti, 2(2), 37–48.
Sofwan, A. (2006). Belajar Mysql dengan Phpmyadmin Pendahuluan. 1–29.
SIHOTANG, H. T. (2019). Sistem Informasi Pengagendaan Surat Berbasis Web Pada Pengadilan Tinggi Medan. 3(1), 6–9. https://doi.org/10.31227/osf.io/bhj5q
Prof. Dr. Sri Haryatmi Kartiko, M.Sc Dr. Zaenal Arifin, S.Pd, M.Pd Siti Amiroch, M. S. (2017). Pengimpletasian phpMyAdmin pada rancangan sistem administrasi surat dengan studi kasus pada LSP Universitas Dr. Soetomo Surabaya. Journal of Mathematics and Computer Science.
Nur, A. A., & Taufik, I. (2024). SISTEM PAKAR DIAGNOSA PENYAKIT AYAM BROILER METODE NAÏVE BAYES BERBASIS WEB. Journal of Composite Social Humanisme, 1(3), 1-8.
Randily, D. R. P., & Rismawan, T. (2025). Implementasi IoT dan Gaussian Naive Bayes Untuk Sistem Monitoring Kandang Ayam Broiler. Jurnal Informatika dan Teknik Elektro Terapan, 13(2).
Alamsyah, T. (2026). Pengaruh Pemberian Probiotik Bakteri Asam Laktat Selulolitik Melalui Air Minum Terhadap Bobot Saluran Pencernaan Broiler (Doctoral dissertation, UNIVERSITAS JAMBI).
Yusuf, A., Sulistyohati, A., & Marsiani, E. S. (2025). SISTEM PAKAR DIAGNOSIS BURUNG PARUH BENGKOK DENGAN METODE FORWARD CHAINING. Jurnal Tera, 5(2), 32-48.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Saiful Bahri, Iddrus Iddrus, Miftah Farid (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
