<![CDATA[Chicken eggs are one of the most popular food ingredients in Indonesia, with demand increasing every year. However, the quality of chicken eggs sold to consumers must be ensured to be safe for consumption. This study utilized the You Only Look Once (YOLO) method from a Convolutional Neural Network (CNN) architecture to detect chicken eggs and determine their quality based on eggshell images. The dataset used in this research included variations in eggshell color corresponding to their quality. Based on the model training results, the best model achieved optimal performance with a mean Average Precision (mAP) of 99.287% for mAP50 and 93.317% for mAP50-95. The results of the study demonstrate that YOLO is capable of detecting the quality of chicken eggs, making it applicable for improving efficiency in the egg-sorting process. This research is expected to contribute significantly to the development of more advanced and effective egg-sorting technology to support the distribution of high-quality eggs to the public.]]>
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