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Soegono, Joaquin Noah
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Computer Science & IT

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Implementation of Convolutional Neural Network Algorithm for Apple Leaf Disease Classification Widjaya, Ageng Cahyo; Wijaya, Kimi Axel; Soegono, Joaquin Noah; Varrel, Primus Kartika; Johan, Monika Evelin
ULTIMA InfoSys Vol 16 No 1 (2025): Ultima InfoSys : Jurnal Ilmu Sistem Informasi
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/si.v16i1.3842

Abstract

Apple leaf diseases can cause significant economic losses to apple farmers. Early detection and treatment of apple leaf diseases are essential to minimize crop losses. However, traditional methods for detecting apple leaf diseases, such as manual visual inspection by experts, can be time-consuming and laborious. Therefore, this study aims to develop a robust and efficient method for detecting diseases in apple tree leaves using Convolutional Neural Networks (CNNs). By using deep learning, the disease detection process becomes automated, saving time and resources. The CRISP-DM methodology was used in conducting this study. The results of the CNN model's performance in predicting disease types have a high level of accuracy and can be used as a model for detecting disease types in apple plant leaves.
Co-Authors Johan, Monika Evelin Varrel, Primus Kartika Widjaya, Ageng Cahyo Wijaya, Kimi Axel