Sinkron : Jurnal dan Penelitian Teknik Informatika
Vol. 6 No. 4 (2022): Article Research: Volume 6 Number 4, October 2022

Classification of beetle type using the Convolutional Neural Network algorithm

Fawwaz, Insidini (Unknown)
Candra, Tomy (Unknown)
Marpaung, Delima Agustina Margareta (Unknown)
Dinis, Arun (Unknown)
Fachrozi, M Reza (Unknown)



Article Info

Publish Date
03 Oct 2022

Abstract

Beetles (Order Coleoptera) are the largest order of animals. Beetles are a group of insects that make up the order Coleoptera. Estimates of the total number of living beetle species are millions of beetle species whose features make it difficult to visually identify beetle species. Currently, the beetle classification process is still carried out using direct observation and personal assumptions. CNN model ResNet50 is one of the ResNet variants that has 50 layers and VGG16 is a CNN model that utilizes a convolutional layer with a small convolutional filter specification (3×3) and always uses the same padding and maxpool layers of a 2x2 filter. In this Algorithm (CNN) with the ResNet50 model, it succeeded in exploring beetles with accuracy, precision, recall and F-1 Score with values of 93%, 94.24%, 89.28%, 91.69%, while the VGG16 model succeeded in conducting research on beetle species with accuracy, precision, recall and F-1 Score with values of 86.9%, 87.5%, 87%, 87.2%, so it can be said that the classification of beetle species using the CNN algorithm with the ResNet50 model is better than the VGG16 model.

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Journal Info

Abbrev

sinkron

Publisher

Subject

Computer Science & IT

Description

Scope of SinkrOns Scientific Discussion 1. Machine Learning 2. Cryptography 3. Steganography 4. Digital Image Processing 5. Networking 6. Security 7. Algorithm and Programming 8. Computer Vision 9. Troubleshooting 10. Internet and E-Commerce 11. Artificial Intelligence 12. Data Mining 13. Artificial ...