Android Application for Tomato Leaf Disease Prediction Based on MobileNet Fine-tuning

Android Application for Tomato Leaf Disease Prediction Based on MobileNet Fine-tuning

deep learning; computer vision; android application; tomato leaf disease

Tomato is one of the most well-known and widely cultivated plants in the world. Tomato production result is affected by the
conditions of the plants when they are cultivated. It may decrease due to leaf plant disease caused by climate change, pollinator
decrease, microbial pets, or parasites. To prevent this, an image-based application is needed to identify tomato plant disease
based on visually unique patterns or marks seen on leaves. In this paper, we proposed a CNN fine-tuned model that is based
on MobileNet architectures to identify tomato leaf disease for mobile applications. Based on the results tested by K-fold crossvalidation, the best accuracy achieved by the proposed model is 97.1%. In addition, the best average precision, recall, and F1
Score are 99.8%, 99.8%, and 99.5% respectively. The model with have best results is also implemented into Android-based mobile applications

Mutia Fadhilla, Des Suryani

http://jurnal.iaii.or.id

Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association

December 2023

Sri Wahyuni

ISSN Media Electronic: 2580-0760

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