Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat)
Nihayah Afarini
Universitas Nasional Jakarta
Computer Science & IT Electrical & Electronics Engineering Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
OPTIMIZATION OF CNN + MOBILENETV3 FOR INSECT IDENTIFICATION: TOWARD HIGH ACCURACY Nihayah Afarini; Djarot Hindarto
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 9 No. 1 (2024)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v9i1.199

Abstract

Developments in the field of artificial intelligence and deep learning, particularly Convolutional Neural Networks (CNN) techniques, have expanded the research potential and applications in ecology, including efficient and accurate insect classification. However, there are challenges in achieving high levels of accuracy with similar computational efficiency. In response, the efficient MobileNetV3 architecture was investigated to improve the insect pest classification process. Through an analytical descriptive quantitative approach and insect datasets from Kaggle, this study tested the effectiveness of CNN models optimized with MobileNetV3. The results indicated that the optimized model achieved classification accuracy of up to 90%, with consistent performance between training and validation data and significant loss reduction. With high precision and processing efficiency, this discovery makes a substantial contribution to deep learning applications in the field of intelligent agriculture, promising methodological improvements for other classification problems. Despite offering a promising solution, this study recognizes the limitation in dataset diversity and suggests further exploration with more varied datasets to strengthen the model's application in actual agricultural practices.
Co-Authors Djarot Hindarto