Pengenalan Jamur Yang Dapat Dikonsumsi Menggunakan Metode Transfer Learning Pada Convolutional Neural Network

Not all mushrooms are edible because some are poisonous. The edible or poisonous mushrooms can be identified by paying attention to the morphological characteristics of mushrooms, such as shape, color, and texture. There is an issue: some poisonous mushrooms have morphological features that are very...

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Autores principales:	Elok Iedfitra Haksoro, Abas Setiawan
Formato:	article
Lenguaje:	EN ID
Publicado:	P3M Politeknik Negeri Banjarmasin 2021
Materias:	convolutional neural network jamur dapat dikonsumsi mobilenets mobilenetv2 transfer learning Electrical engineering. Electronics. Nuclear engineering TK1-9971 Information technology T58.5-58.64
Acceso en línea:	https://doaj.org/article/f097ec3d6a0a430eb8b305d1107ed144
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

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spelling	oai:doaj.org-article:f097ec3d6a0a430eb8b305d1107ed1442021-12-02T17:25:02ZPengenalan Jamur Yang Dapat Dikonsumsi Menggunakan Metode Transfer Learning Pada Convolutional Neural Network2598-32452598-328810.31961/eltikom.v5i2.428https://doaj.org/article/f097ec3d6a0a430eb8b305d1107ed1442021-09-01T00:00:00Zhttps://eltikom.poliban.ac.id/index.php/eltikom/article/view/428https://doaj.org/toc/2598-3245https://doaj.org/toc/2598-3288Not all mushrooms are edible because some are poisonous. The edible or poisonous mushrooms can be identified by paying attention to the morphological characteristics of mushrooms, such as shape, color, and texture. There is an issue: some poisonous mushrooms have morphological features that are very similar to edible mushrooms. It can lead to the misidentification of mushrooms. This work aims to recognize edible or poisonous mushrooms using a Deep Learning approach, typically Convolutional Neural Networks. Because the training process will take a long time, Transfer Learning was applied to accelerate the learning process. Transfer learning uses an existing model as a base model in our neural network by transferring information from the related domain. There are Four base models are used, namely MobileNets, MobileNetV2, ResNet50, and VGG19. Each base model will be subjected to several experimental scenarios, such as setting the different learning rate values for pre-training and fine-tuning. The results show that the Convolutional Neural Network with transfer learning method can recognize edible or poisonous mushrooms with more than 86% accuracy. Moreover, the best accuracy result is 92.19% obtained from the base model of MobileNetsV2 with a learning rate of 0,00001 at the pre-training stage and 0,0001 at the fine-tuning stage.Elok Iedfitra HaksoroAbas SetiawanP3M Politeknik Negeri Banjarmasinarticleconvolutional neural networkjamur dapat dikonsumsimobilenetsmobilenetv2transfer learningElectrical engineering. Electronics. Nuclear engineeringTK1-9971Information technologyT58.5-58.64ENIDJurnal ELTIKOM: Jurnal Teknik Elektro, Teknologi Informasi dan Komputer, Vol 5, Iss 2, Pp 81-91 (2021)
institution	DOAJ
collection	DOAJ
language	EN ID
topic	convolutional neural network jamur dapat dikonsumsi mobilenets mobilenetv2 transfer learning Electrical engineering. Electronics. Nuclear engineering TK1-9971 Information technology T58.5-58.64
spellingShingle	convolutional neural network jamur dapat dikonsumsi mobilenets mobilenetv2 transfer learning Electrical engineering. Electronics. Nuclear engineering TK1-9971 Information technology T58.5-58.64 Elok Iedfitra Haksoro Abas Setiawan Pengenalan Jamur Yang Dapat Dikonsumsi Menggunakan Metode Transfer Learning Pada Convolutional Neural Network
description	Not all mushrooms are edible because some are poisonous. The edible or poisonous mushrooms can be identified by paying attention to the morphological characteristics of mushrooms, such as shape, color, and texture. There is an issue: some poisonous mushrooms have morphological features that are very similar to edible mushrooms. It can lead to the misidentification of mushrooms. This work aims to recognize edible or poisonous mushrooms using a Deep Learning approach, typically Convolutional Neural Networks. Because the training process will take a long time, Transfer Learning was applied to accelerate the learning process. Transfer learning uses an existing model as a base model in our neural network by transferring information from the related domain. There are Four base models are used, namely MobileNets, MobileNetV2, ResNet50, and VGG19. Each base model will be subjected to several experimental scenarios, such as setting the different learning rate values for pre-training and fine-tuning. The results show that the Convolutional Neural Network with transfer learning method can recognize edible or poisonous mushrooms with more than 86% accuracy. Moreover, the best accuracy result is 92.19% obtained from the base model of MobileNetsV2 with a learning rate of 0,00001 at the pre-training stage and 0,0001 at the fine-tuning stage.
format	article
author	Elok Iedfitra Haksoro Abas Setiawan
author_facet	Elok Iedfitra Haksoro Abas Setiawan
author_sort	Elok Iedfitra Haksoro
title	Pengenalan Jamur Yang Dapat Dikonsumsi Menggunakan Metode Transfer Learning Pada Convolutional Neural Network
title_short	Pengenalan Jamur Yang Dapat Dikonsumsi Menggunakan Metode Transfer Learning Pada Convolutional Neural Network
title_full	Pengenalan Jamur Yang Dapat Dikonsumsi Menggunakan Metode Transfer Learning Pada Convolutional Neural Network
title_fullStr	Pengenalan Jamur Yang Dapat Dikonsumsi Menggunakan Metode Transfer Learning Pada Convolutional Neural Network
title_full_unstemmed	Pengenalan Jamur Yang Dapat Dikonsumsi Menggunakan Metode Transfer Learning Pada Convolutional Neural Network
title_sort	pengenalan jamur yang dapat dikonsumsi menggunakan metode transfer learning pada convolutional neural network
publisher	P3M Politeknik Negeri Banjarmasin
publishDate	2021
url	https://doaj.org/article/f097ec3d6a0a430eb8b305d1107ed144
work_keys_str_mv	AT elokiedfitrahaksoro pengenalanjamuryangdapatdikonsumsimenggunakanmetodetransferlearningpadaconvolutionalneuralnetwork AT abassetiawan pengenalanjamuryangdapatdikonsumsimenggunakanmetodetransferlearningpadaconvolutionalneuralnetwork
_version_	1718380942549057536

Pengenalan Jamur Yang Dapat Dikonsumsi Menggunakan Metode Transfer Learning Pada Convolutional Neural Network

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