Detection of the Types of Consumable Saltwater Fish in the Coastal Area of Likupang Uses the Convolutional Neural Network Method

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Liza Wikarsa
Apriandy Angdresey
Ticoalu Sombouwadil

Abstract

In the coastal area of Likupang, many types of saltwater fish can be consumed, such as tuna and skipjack. Yet, there are also types of saltwater fish that cannot be consumed or protected by the government, such as Napoleon fish and sea kingfish. Thus, this research aimed to build a desktop application that can automatically classify consumable and non-consumable saltwater fish species more accurately and promptly using a suitable image recognition method like the Convolutional Neural Network (CNN). CNN has abilities to distinguish images by recognizing several pixels in a two-dimensional image and RGB (Red, Green, Blue) colors which are then converted into a matrix with various values, making it easier for the system to recognize the two-dimensional image. By using 40% test data (143 images) and 60% training data (213 images), test accuracy in identifying and classifying images of consumable fish, non-consumable fish, and non-fish images with each percentage of 94%, 98%, and 95% respectively.


 


 

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How to Cite
Wikarsa, L., Angdresey, A., & Sombouwadil , T. (2022). Detection of the Types of Consumable Saltwater Fish in the Coastal Area of Likupang: Uses the Convolutional Neural Network Method. Jurnal Pekommas, 7(2). https://doi.org/10.56873/jpkm.v7i2.4884
Section
Informatics
Author Biographies

Liza Wikarsa, Universitas Katolik De La Salle Manado

Informatics Engineering Study Programmee

Faculty of Engineering

 

Apriandy Angdresey, Universitas Katolik De La Salle Manado

Full-time lecturer at Informatics Engineering Study Programme, Faculty of Engineering

Ticoalu Sombouwadil , Universitas Katolik De La Salle Manado

Student at Informatics Engineering Study Programme, Faculty of Engineering

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