Intelligent Agriculture

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Automatic Identification of Aceh Cattle Using an Image-Based Computer Vision Approach for Smart Livestock Management

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https://doi.org/10.54963/ia.v2i1.2409
Volume 2 Issue 1 (2026): In Progress
Copyright (c) 2026 Muhammad Ammar, Eka Meutia Sari, Cut Intan Novita, Mohd. Agus Nashri Abdullah, Hendra Koesmara, Yenni Yusriani, Masduqi Masduqi
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Authors

  • Muhammad Ammar

    Animal Science Department, Agriculture Faculty, Universitas Syiah Kuala, Banda Aceh 23111, Indonesia
    Research Center Aceh Cattle and Local Livestock, Universitas Syiah Kuala, Banda Aceh 23111, Indonesia
  • Eka Meutia Sari

    Animal Science Department, Agriculture Faculty, Universitas Syiah Kuala, Banda Aceh 23111, Indonesia
    Research Center Aceh Cattle and Local Livestock, Universitas Syiah Kuala, Banda Aceh 23111, Indonesia
  • Cut Intan Novita

    Animal Science Department, Agriculture Faculty, Universitas Syiah Kuala, Banda Aceh 23111, Indonesia
    Research Center Aceh Cattle and Local Livestock, Universitas Syiah Kuala, Banda Aceh 23111, Indonesia
  • Mohd. Agus Nashri Abdullah

    Animal Science Department, Agriculture Faculty, Universitas Syiah Kuala, Banda Aceh 23111, Indonesia
    Research Center Aceh Cattle and Local Livestock, Universitas Syiah Kuala, Banda Aceh 23111, Indonesia
  • Hendra Koesmara

    Research Center Aceh Cattle and Local Livestock, Universitas Syiah Kuala, Banda Aceh 23111, Indonesia
    Diploma Program in Livestock Production, Agriculture Faculty, Universitas Syiah Kuala, Banda Aceh 23111, Indonesia
  • Yenni Yusriani

    Research Center Aceh Cattle and Local Livestock, Universitas Syiah Kuala, Banda Aceh 23111, Indonesia
    Research Center for Animal Husbandry, National Research and Innovation Agency of the Republic of Indonesia, Cibinong 16911, Indonesia
  • Masduqi Masduqi

    Research Center Aceh Cattle and Local Livestock, Universitas Syiah Kuala, Banda Aceh 23111, Indonesia
    Department of Livestock, Government of Aceh Province, Banda Aceh 23245, Indonesia

Received: 13 December 2025; Revised: 27 January 2026; Accepted: 9 February 2026; Published: 26 March 2026

The identification of cattle breeds is an important aspect of livestock management, particularly for maintaining genetic resources and supporting breeding programs of local cattle. In Indonesia, Aceh cattle represent one of the important indigenous breeds whose identification is commonly conducted through manual observation based on physical characteristics. However, conventional identification methods often depend on human expertise and may lead to inconsistencies or misclassification. Recent advances in artificial intelligence, especially in computer vision technologies, provide new opportunities to develop automated systems for livestock identification. This study aims to develop an image-based classification model to distinguish Aceh cattle from non-Aceh cattle using computer vision techniques. A dataset of cattle images was collected from field documentation and various online sources and categorized into two classes. After the image collection process was completed, image adjustment and augmentation processes followed, resulting in a final dataset of 2,360 images, which were used for model training and testing. The dataset consisted of 800 original images expanded through augmentation techniques and was automatically divided into training and validation datasets using an 80:20 ratio. The classification model was developed using Teachable Machine and evaluated using performance metrics such as accuracy, precision, and recall. The experimental results show that the model achieved an accuracy of 89.6%, with precision and recall values of 89.1% and 90.3%, respectively. The findings demonstrate the feasibility of applying low-code artificial intelligence platforms for indigenous cattle breed classification in digital livestock management systems.

Keywords:

Aceh Cattle Computer Vision Image Classification Livestock Identification Smart Agriculture Precision Livestock Farming

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