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

Tomato is one of the most well-known and widely cultivated plants in the world. The result of tomato production is affected by the conditions of the plants when they are grown. It may decrease due to leaf plant disease caused by climate change, pollinator decrease, microbial pets, or parasites. To p...

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Main Authors: Mutia Fadhilla, Des Suryani
Format: Article
Language:English
Published: Ikatan Ahli Informatika Indonesia 2023-11-01
Series:Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Subjects:
Online Access:https://jurnal.iaii.or.id/index.php/RESTI/article/view/5132
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author Mutia Fadhilla
Des Suryani
author_facet Mutia Fadhilla
Des Suryani
author_sort Mutia Fadhilla
collection DOAJ
description Tomato is one of the most well-known and widely cultivated plants in the world. The result of tomato production is affected by the conditions of the plants when they are grown. 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 based on MobileNet architectures to identify tomato leaf disease for mobile applications. Based on the results tested by K-fold cross-validation, the best accuracy achieved by the proposed model is 97.1%. Additionally, the best average precision, recall and F1 Score are 99.8%, 99.8%, and 99.5%, respectively. The model with the best results is also implemented into Android-based mobile applications.
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spelling doaj.art-a502bc1d98304816900f3fca23fa4a1b2024-02-03T14:53:00ZengIkatan Ahli Informatika IndonesiaJurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)2580-07602023-11-01761260126710.29207/resti.v7i6.51325132Android Application for Tomato Leaf Disease Prediction Based on MobileNet Fine-tuningMutia Fadhilla0Des Suryani1Universitas Islam RiauUniversitas Islam RiauTomato is one of the most well-known and widely cultivated plants in the world. The result of tomato production is affected by the conditions of the plants when they are grown. 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 based on MobileNet architectures to identify tomato leaf disease for mobile applications. Based on the results tested by K-fold cross-validation, the best accuracy achieved by the proposed model is 97.1%. Additionally, the best average precision, recall and F1 Score are 99.8%, 99.8%, and 99.5%, respectively. The model with the best results is also implemented into Android-based mobile applications.https://jurnal.iaii.or.id/index.php/RESTI/article/view/5132deep learningcomputer visionandroid applicationtomato leaf disease
spellingShingle Mutia Fadhilla
Des Suryani
Android Application for Tomato Leaf Disease Prediction Based on MobileNet Fine-tuning
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
deep learning
computer vision
android application
tomato leaf disease
title Android Application for Tomato Leaf Disease Prediction Based on MobileNet Fine-tuning
title_full Android Application for Tomato Leaf Disease Prediction Based on MobileNet Fine-tuning
title_fullStr Android Application for Tomato Leaf Disease Prediction Based on MobileNet Fine-tuning
title_full_unstemmed Android Application for Tomato Leaf Disease Prediction Based on MobileNet Fine-tuning
title_short Android Application for Tomato Leaf Disease Prediction Based on MobileNet Fine-tuning
title_sort android application for tomato leaf disease prediction based on mobilenet fine tuning
topic deep learning
computer vision
android application
tomato leaf disease
url https://jurnal.iaii.or.id/index.php/RESTI/article/view/5132
work_keys_str_mv AT mutiafadhilla androidapplicationfortomatoleafdiseasepredictionbasedonmobilenetfinetuning
AT dessuryani androidapplicationfortomatoleafdiseasepredictionbasedonmobilenetfinetuning