Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal G-Tech : Jurnal Teknologi Terapan
Royan, Yusuf Iskandar
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management Energy Engineering

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

Found 1 Documents
Search

 1 
Performance Comparison of Convolutional Neural Networks (CNN) and Support Vector Machine (SVM) Algorithms in Human Face Classification Royan, Yusuf Iskandar; Pramono, Pramono; Asri, Anindhiasti Ayu Kusuma
G-Tech: Jurnal Teknologi Terapan Vol 9 No 3 (2025): G-Tech, Vol. 9 No. 3 July 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v9i3.7384

Abstract

Facial expression recognition is crucial in fields like mental health monitoring and human-computer interaction. This study compares Convolutional Neural Networks (CNN) and Support Vector Machine (SVM) in classifying facial images into stress and non-stress categories. Using a preprocessed dataset of labeled facial expressions, CNN was employed for its strength in automatic spatial feature extraction, while SVM served as a traditional machine learning benchmark. Both models were trained and tested on the same dataset split. Results showed CNN outperformed SVM in all performance metrics: CNN achieved 88.94% accuracy, 94.42% precision, 93.25% recall, and an F1-score of 89.85%, while SVM recorded 76.53% accuracy, 77.14% precision, 85.72% recall, and an F1-score of 80.67%. Despite its lower performance, SVM had faster training and a simpler structure, making it suitable for resource-limited scenarios. The study emphasizes the superiority of deep learning for complex image classification tasks.
Co-Authors Anindhiasti Ayu Kusuma Asri Pramono Pramono