Early Detection of Disease in Chicks Using CNN on Bangkok Chicken Health
DOI:
https://doi.org/10.12928/biste.v6i2.10245Keywords:
Bangkok Chicken, CNN, Early Detection of Disease, Identification, FarmAbstract
Bangkok Chicken (Gallus Gallus Domesticus) is a type of chicken in Indonesia that has a high source of protein and supports the community's economy. The growth and development phase of chicks is a critical period because chicks are very vulnerable to attacks by infectious and non-infectious diseases. These diseases can cause high mortality rates and cause significant economic losses for farmers. This study aimed to investigate the potential for using CNN technology in the early detection of disease in Bangkok chicks in the Ponorogo district. As an artificial neural network, CNN can recognize patterns in visual data with high accuracy. The use of CNN technology in the agricultural sector, including animal husbandry, has shown promising results in supporting early disease detection systems in livestock. This study aims to investigate the potential of using CNN technology in the early detection of disease in Bangkok chicks in the Ponorogo district. By processing visual data from chicken images, CNN will be trained to identify early signs of disease in chicks. The result of this research is that this research can help maintain the availability and security of animal food supplies, which is an essential component of overall food security. In addition, by reducing losses caused by disease, this research can contribute to sustainable agriculture by ensuring the continuation of stable and sustainable animal food production.
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