Implementasi Transfer Learning Dalam Klasifikasi Penyakit Pada Daun Teh Menggunakan MobileNetV2 - Dwijayana, I Gede Diva; Wibawa, I Gede Arta (Jurnal Nasional Teknologi Informasi dan Aplikasnya; Vol 1 No 1 (2022): JNATIA Vol. 1, No. 1, November 2022DO - 10.24843/JNATIA.2022.v01.i01.p45, 2022)
Indonesia is currently the seventh largest tea producer in the world. However, tea farmers in Indonesia still use old technology and simple farming methods. Limited knowledge of small farmers about diseases that can attack their tea leaves. a tool is needed to classify the types of tea leaf diseases using digital images. This research uses a deep learning approach with Convolutional Neural Network using MobileNetV2 architecture for tea leaf disease classification with digital image data. With the transfer learning method, the MobileNetV2 model is trained with 3 different epochs. The best accuracy is obtained from the model trained with epoch 20 with an accuracy value of 94.6% with a loss value of 0.287. The MobileNetV2 model that has been trained shows good results in classifying tea leaf diseases.