Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Journal of Intelligent Systems for Community Development (JISCoDe)
Sultan Ahmad Rizki Badani
Universitas Bhayangkara Jakarta Raya

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

Found 1 Documents
Search

 1 
Road Damage Segmentation Using U-Net and FCN Based on Digital Imagery Sultan Ahmad Rizki Badani; Herlawati Herlawati; Sugiyatno Sugiyatno
Journal of Intelligent Systems for Community Development Vol. 1 No. 1 (2026): 2026: JISCoDe Volume 1 Issue 1 Year 2026
Publisher : Indonesian Artificial Neural Network Society

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Road damage is an infrastructure problem that affects public safety and transportation mobility. Manual road damage identification is considered less effective because it is time-consuming and subjective. This study aimed to implement semantic segmentation using the U-Net and Fully Convolutional Network (FCN) architectures for road damage detection based on digital images. The research used the Cross Industry Standard Process for Data Mining (CRISP-DM) method with datasets consisting of secondary PotholeMix data and primary data collected in West Bekasi. Model training was conducted using 256×256 pixel images with evaluation metrics including Accuracy, Dice Score Coefficient, Intersection over Union (IoU), and Loss. The results showed that the U-Net model achieved better performance than FCN with an Accuracy of 0.9652, Dice Score Coefficient of 0.9596, IoU of 0.9267, and Loss of 0.0674. Furthermore, the model was successfully implemented into a Flutter-based mobile application for automatic road damage identification and monitoring.
Co-Authors Herlawati Herlawati Sugiyatno Sugiyatno