Deteksi Kesegaran Telur Ayam pada Citra Cangkang Menggunakan Metode Convolutional Neural Network (CNN)

This research developed an egg freshness detection system using the Convolutional Neural Network (CNN) method to analyze egg shell images. A dataset consisting of 1,898 images of fresh and stale egg shells was used in this study. The pre-processing stage included resizing and labeling data, followed by training the CNN model using the SqueezeNet and AlexNet architectures. The results showed an accuracy of 90% in classifying egg freshness. The use of CNN proved to be more effective than conventional methods such as thresholding and K-Nearest Neighbor (KNN). This research makes a significant contribution to improving the efficiency and accuracy of egg sorting in Indonesia, reducing reliance on manual methods, and speeding up the sorting process.