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All Journal JOIV : International Journal on Informatics Visualization International Journal of Artificial Intelligence Research PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer JURNAL PENDIDIKAN TAMBUSAI Journal of Information Technology and Computer Engineering JURTEKSI Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Review Pendidikan dan Pengajaran (JRPP) Jusikom: Jurnal Sistem Informasi Ilmu Komputer JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Infortech Jurnal Pendidikan Guru (JPG) Journal of Applied Data Sciences Journal of Computer Scine and Information Technology Bulletin of Computer Science Research Jurnal Pustaka Data : Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitektur Komputer Jurnal Pustaka AI : Pusat Akses Kajian Teknologi Artificial Intelligence Jurnal Komtekinfo Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
Sovia, Rini
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Social Sciences Other

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ANALISIS KUALITAS PRODUKSI AYAM BROILER MENGGUNAKAN METODE K-MEANS CLUSTERING DAN ALGORITMA C4.5 Saputra, Oriza Rama; Sovia, Rini; Yanto, Musli
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 9, No 1 (2026): February 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i1.5747

Abstract

Abstract: Broiler chicken production is influenced by various factors, such as feed, environment, and maintenance management, which generate large amounts of complex production data. This condition causes the assessment and decision-making processes related to production quality to often be suboptimal and not based on in-depth data analysis. This study aims to implement the K-Means method and C4.5 algorithm to produce an analysis process that can be used as a solution in determining broiler chicken production quality in the South Coast region. The K-Means method is used to classify broiler chicken production data based on similar characteristics to facilitate pattern identification. The C4.5 algorithm was used to build a decision tree model to determine and predict broiler chicken production quality based on the most influential attributes. The research dataset was sourced from farm data in the South Coast region, with a total of 157 data points obtained. The clustering results presented three main segments, namely 94 with good results, 58 data with moderate results, and 5 data with poor results. Meanwhile, the C4.5 algorithm was built based on the clustering results from K-Means. The accuracy was calculated using the F1 score, with an accuracy of 93,75%. Keywords: Broiler Chicken;K-Means; C4.5 Algorithm. Abstrak: Produksi ayam broiler dipengaruhi oleh berbagai faktor, seperti pakan, lingkungan, dan manajemen pemeliharaan, yang menghasilkan data produksi dalam jumlah besar dan bersifat kompleks. Kondisi ini menyebabkan proses penilaian dan pengambilan keputusan terkait kualitas produksi sering kali belum optimal dan kurang didasarkan pada analisis data yang mendalam. Penelitian dilakukan bertujuan untuk Mengimplementasikan metode K-Means dan algoritma C4.5 untuk menghasilkan proses analisis yang dijadikan solusi dalam penentuan kualitas produksi ayam broiler di wiliyah Pesisir Selatan. Metode K-Means digunakan untuk mengklasifikasikan data produksi ayam broiler berdasarkan kesamaan karakteristik untuk memudahkan identifikasi pola. Algoritma C4.5 Digunakan untuk membangun model pohon keputusan dalam menentukan dan memprediksi kualitas produksi ayam broiler berdasarkan atribut yang paling berpengaruh. Dataset penelitian bersumber dari data peternakan di wilayah Pesisir Selatan, Dengan total data ada 157 data yang didapatkan. Hasil klustering menyajikan tiga segmen utama yaitu 94 dengan hasil baik, 58 data dengan hasil sedang dan 5 data dengan hasil buruk, Sedangkan Algoritma C4.5 dibangun berdasarkan hasil klustering dari K-Means. Perhitungan Hasil akurasi dengan f1 score Dengan hasil akurasi 93,75%. Kata Kunci: Ayam Broiler, K-Means, Algoritma C4.5
Co-Authors Adinda Syalsabila Aditra Agus Salim, David Al-arrafi, Muhammad Ikhsan Amin Amirul Mukminin, Andi Anam, M Khairul Awal, Hasri Borianto, B Chairunnissa Deliva Akbar, Syifa Devia Kartika Dila, Rahmah Effendy, Geraldo Revanska Elmi Rahmawati, Elmi Erlanda, Hadrian Fana, Wulan Stau Fatimah, Noor Gema, Rima Liana Gunadi Widi Nurcahyo Gusriva, Revi Hadi, Aulia Fitrul Hadiyanto, Tegas Harnaranda, Jefri Hartika Zain, Ruri Hartika Hendri Irawan Hendrik, Billy Huda, Ramzil Irzal Arief Wisky Islam, Md Ataul Khomsi, Ahmad Lubis, Fitri Amelia Sari maha rani Nugraha, Fajri Nurdiansyah, Ali Nursyahrina Permana, Randi Permana, Randy Putra, Kharisma Utama Rahmad Rahmad Rahman, Muhammad Aidil Rahman, Zumardi Rahmi, Nadya Alinda Ramadani, Sela Ramadhanu, Agung - Ricki Ardiansyah, Ricki Ridwan Sutri Rinaldi Chan, Fajri Rindhani Aditia, Mellya Riyan Saputra Riyan Saputra, Riyan Roza, Yesi Betriana Rozakh, Muhammad Ruri Hartika Zain S, Sumijan Sandawa, Hoka Muhgrah Saputra, Charisman Fajri Saputra, Oriza Rama Saputra, Randy Sarjon Defit Selfi Melisa Selvia, Dina Siregar, Diffri Sumijan Sutri, Ridwan Syafril Syafril Syaiffullah, Afif Tika Christy Wahyudi, Anggy Wirdawati, Wira Yanti, Rahma Yanto, Musli Yasmin, Nabilla Yenila, Firna Yuhandri Yuhandri Yuhandri, Yuhandri Yuhandri, Y