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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Djuliani, Ayu
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Computer Science & IT Engineering

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Classification of Cihateup duck egg fertility using convolutional neural network EfficientNet-B3 Dewi Sri Mulyani, Evi; Mufizar, Teuku; Rohpandi, Dani; Djuliani, Ayu; Rahmatulloh, Egi; Satia Aulia Rahmat, Rinaldi
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 1: February 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i1.pp798-809

Abstract

Accurate detection of egg fertility is crucial to improve hatching success in duck farming. Conventional candling methods rely heavily on human expertise, making them subjective and error-prone. This study proposes an automated classification system for Cihateup duck egg fertility using candling images and a convolutional neural network (CNN) based on the EfficientNet-B3 architecture. Image enhancement techniques, including contrast limited adaptive histogram equalization (CLAHE), unsharp masking, and adaptive thresholding, were applied to improve image quality and feature visibility. The dataset consisted of fertile and infertile egg images captured at two incubation stages: the first 24 hours and the 8th–15th days. Data were split into training, validation, and testing sets with a ratio of 70:15:15. Experimental results show that image enhancement significantly improves classification performance. Without enhancement, the model achieved an accuracy of 49% with an area under curve (AUC) of 0.4226, indicating poor discrimination capability. With image enhancement, the proposed method achieved accuracies of 77% for the first 24 hours dataset and 80% for the 8th–15th days dataset, with AUC values of 0.9962 and 0.9317, respectively. These results demonstrate that EfficientNet-B3 combined with image enhancement provides an effective and computationally efficient solution for automated fertility detection of Cihateup duck eggs.
Co-Authors Dani Rohpandi Evi Dewi Sri Mulyani Rahmatulloh, Egi Satia Aulia Rahmat, Rinaldi Teuku Mufizar