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

Sincan  Maulana

doi:10.70294/jimu.v2i04.441

Penulis

Sincan Maulana Universitas Muhammadiyah Ponorogo

DOI:

https://doi.org/10.70294/jimu.v2i04.441

Kata Kunci:

CNN, chicken eggs, shell images, deep learning

Abstrak

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.

Unduhan

Data unduhan belum tersedia.

Referensi

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