Article Per Year (5 Year)
p-Index From 2021 - 2026
3.138
P-Index
This Author published in this journals
All Journal Jurnal Ilmiah Informatika Komputer International Journal of Advances in Intelligent Informatics Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Journal of System and Computer Engineering Jurnal Pengabdian Masyarakat Indonesia Jurnal Abdi Masyarakat Indonesia Buletin Sistem Informasi dan Teknologi Islam Ilmu Komputer untuk Masyarakat Jurnal Fokus Elektroda (Energi Listrik, Telekomunikasi, Komputer, Elektronika dan Kendali) Bulletin of Social Informatics Theory and Application JBIMA: Jurnal Pengabdian kepada Masyarakat Linier: Literatur Informatika dan Komputer
Ramdaniah Ramdaniah
Teknik Informatika, Fakultas Ilmu Komputer, Universitas Muslim Indonesia
Aerospace Engineering Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Mathematics Public Health Social Sciences Other

Published : 19 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : journal of system and computer engineering

 1 
Enhancing Polyp Segmentation Using Attention U-Net with CLAHE Ramdaniah Ramdaniah; Bayu Adrian Ashad
Journal of System and Computer Engineering Vol 7 No 1 (2026): JSCE: January 2026
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v7i1.2370

Abstract

Colorectal cancer remains one of the leading causes of death worldwide, where early detection of polyps through colonoscopy plays a vital role in prevention. This study aims to enhance polyp segmentation performance by integrating Attention U-Net with Contrast Limited Adaptive Histogram Equalization (CLAHE) as a preprocessing technique. The proposed method was evaluated using two benchmark datasets, CVC-ClinicDB as the primary dataset and Kvasir-SEG for cross-domain testing. The model was trained using a combination of Binary Cross-Entropy and Dice losses, with a 70–15–15 split for training, validation, and testing. Experimental results show that applying CLAHE improves segmentation accuracy, achieving Dice and IoU scores of 0.84 and 0.76 on CVC-ClinicDB, and 0.62 and 0.50 on Kvasir-SEG, respectively. Statistical analysis using the Wilcoxon signed-rank test confirmed a significant difference between the baseline and enhanced models. These findings demonstrate that the integration of CLAHE with Attention U-Net effectively improves boundary detection and robustness against illumination variations across datasets, contributing to more accurate and reliable computer-aided diagnosis in colorectal cancer screening.
Co-Authors Andi Aditya Warman Fachran Talan Andi Cici Amalia Azmi Fauziah Nur Bayu Adrian Ashad Dolly Indra Dwi Maharani Muslim Erika Riski Melani Farniwati Fattah Harlinda Lahuddin Irawati Irawati Lutfi Budi Ilmawan, Lutfi Budi Mansur Miftahul Janna Mubarak, Syahrul Muh Rizaldi Sahari Muhammad Arfah Asis Muhammad Fadhly Amiruddin Muhammad Farhan Hermansyah Mustari, Muhid Nia Kurniati Nur Ainun Zulkarnain Purnawansyah Purnawansyah Rainanda Darya Saputra Saidah Suyuti Siska Anraeni Sitti Hajrah Mansyur Sriwijanaka Sriwijanaka Sriwijanaka St. Hajrah Mansyur Sukur, Widianti Syarif Hidayah Tasrif Hasanuddin Tazkirah Amaliah Yulita Salim