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All Journal INTEGRATIF: Jurnal Pengabdian Kepada Masyarakat Journal of Computing Innovations and Emerging Technologies
Cepi Ramdani
Politeknik Manufaktur Bandung
Computer Science & IT Education Social Sciences Other

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Performance Evaluation of CLAHE-Enhanced Edge Detection on Low-Light Faces Duddy Arisandi; Ahshonat Khoerunnisa; Ruminto Subekti; Aan Eko Setiawan; Cepi Ramdani
Journal of Computing Innovations and Emerging Technologies Vol. 1 No. 1 (2025): Volume 1 No 1
Publisher : novamindpress

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64472/jciet.v1i1.2

Abstract

Edge detection is an important early stage in an image processing-based face detection system. However, the quality of edge detection is highly dependent on the lighting and contrast of the input image. A common problem is the low contrast quality of facial images, which causes edge detection results to be suboptimal, especially in low-light images. This study evaluates the effect of the use of the Contrast Limited Adaptive Histogram Equalization (CLAHE) method on edge detection performance using Canny operators. Two scenarios were tested: edge detection without preprocessing and edge detection after image processing with CLAHE. Evaluation was carried out using two metrics: the number of contours and the total area of the contours of the detected results. The test results showed that the use of CLAHE consistently increased the number of contours and stabilized the contour area distribution, indicating an increased sensitivity to facial edge details. Although an increase in the number of contours can increase the risk of noise detection, the results suggest that CLAHE is able to clarify facial structures that were previously uncaptured. CLAHE has proven to be effective as an image enhancement method in edge detection-based facial detection systems
Peningkatan Kompetensi Digital Siswa Sekolah Menengah Atas Melalui Pelatihan Koding dan Kecerdasan Buatan: Program Bina Talenta Indonesia Ihsan Tanama Sitio; Danu Jaya Saputro; Muhammad Giriarda Abrari; Cepi Ramdani; Noer Fajrin
INTEGRATIF: Jurnal Pengabdian Kepada Masyarakat Vol 4 No 1 (2026): INTEGRATIF: Jurnal Pengabdian Kepada Masyarakat
Publisher : Kilau Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60041/integratif.v4i1.474

Abstract

This community service program aimed to develop the potential of senior high school students in the fields of coding and artificial intelligence (AI). The hands-on training was conducted online via Zoom Meetings for synchronous sessions and an LMS for quizzes and exercises from September 15 to November 25, 2025. 60 senior high school students from 13 provinces across Indonesia participated and were divided into three classes. The results indicate that students’ knowledge increased substantially, as reflected in the improvement in mean test scores across all classes: from 54.87 to 83.13 in Class A, from 65.31 to 80.56 in Class B, and from 62.83 to 70.93 in Class C. The program demonstrated a significant positive impact, particularly in enhancing participants’ knowledge of artificial intelligence (AI) and coding, as well as their technical skills and character development.
Co-Authors Aan Eko Setiawan Ahshonat Khoerunnisa Danu Jaya Saputro Duddy Arisandi Ihsan Tanama Sitio Muhammad Giriarda Abrari Noer Fajrin RUMINTO SUBEKTI