Identification of Grouper Fish Types using Convolutional Neural Network Resnet-50 Algorithm

Grouper is a type of fish that is popular with the public. It is necessary to identify the type of grouper fish based on color patterns with increase the epoch value to get the best accuracy. The purpose of the research is to predict the type of grouper. This research use CNN Resnet-50 algorithm. 30 data used. The accuracy of prediction is 75 % to predict the image groupers. In the grouper prediction process, the more we increase the epoch value, we will get the best accuracy value. Epoch is a factor that affects the time of training an AI model and affects the accuracy value of the AI model.

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Publication Details

Journal
JURNAL SISTEM INFORMASI BISNIS
Published
2025-04-15
DOI
https://doi.org/10.14710/vol15iss2pp173-178
Primary Topic
Water Quality Monitoring Technologies
Type
article
Field-Weighted Citation Impact
0.00
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article

Identification of Grouper Fish Types using Convolutional Neural Network Resnet-50 Algorithm

I Kadek Noppi Adi Jaya, Adi Wibowo, Rini Nuraini, Wahyul Amien Syafei
JURNAL SISTEM INFORMASI BISNIS
Water Quality Monitoring Technologies
article

Identification of Grouper Fish Types using Convolutional Neural Network Resnet-50 Algorithm

I Kadek Noppi Adi Jaya, Adi Wibowo, Rini Nuraini, Wahyul Amien Syafei
article en

Abstract

Grouper is a type of fish that is popular with the public. It is necessary to identify the type of grouper fish based on color patterns with increase the epoch value to get the best accuracy. The purpose of the research is to predict the type of grouper. This research use CNN Resnet-50 algorithm. 30 data used. The accuracy of prediction is 75 % to predict the image groupers. In the grouper prediction process, the more we increase the epoch value, we will get the best accuracy value. Epoch is a factor that affects the time of training an AI model and affects the accuracy value of the AI model.

JURNAL SISTEM INFORMASI BISNISVol. 15(2)
Diponegoro University (ID), IPB University (ID), Nasional University (ID)
Openalex Percentile: Top 86%
Water Quality Monitoring Technologies
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