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All Journal Jurnal Teknologi Lingkungan Universitas Trisakti AJIE (Asian Journal of Innovation and Entrepreneurship) Jurnal Sains Dan Teknologi Lingkungan CESS (Journal of Computer Engineering, System and Science) Jurnal Sains & Teknologi Lingkungan Jurnal Ilmiah KOMPUTASI INTEGER: Journal of Information Technology Jurnal Sains dan Informatika JSiI (Jurnal Sistem Informasi) Al-Ard: Jurnal Teknik Lingkungan JUSIM (Jurnal Sistem Informasi Musirawas) Journal of Information Systems and Informatics JUKANTI (Jurnal Pendidikan Teknologi Informasi) Prosiding National Conference for Community Service Project Jurnal Pena Indonesia JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) INSERT: Information System and Emerging Technology Journal Telcomatics Journal of Information System and Technology (JOINT) Khazanah: Jurnal Mahasiswa INDONESIAN JOURNAL OF URBAN AND ENVIRONMENTAL TECHNOLOGY Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Social Engagement: Jurnal Pengabdian Kepada Masyarakat Madani: Jurnal Pengabdian Masyarakat dan Kewirausahaan
Andik Yulianto
Universitas Islam Indonesia, Indonesia
Religion Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Transportation Other

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Journal : Journal of Information Systems and Informatics

 1 
Evaluating YOLOv5 and YOLOv8: Advancements in Human Detection Ma Muriyah, Nimatul; Sim, Joel Hamim; Yulianto, Andik
Journal of Information System and Informatics Vol 6 No 4 (2024): December
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i4.944

Abstract

The YOLO (You Only Look Once) method is a state-of-the-art approach in real- time object detection, known for its high-speed image processing capabilities. Recently YOLO versions have differed in performance, particularly in terms of detection accuracy and computational efficiency. The objective of this study is to assess the effectiveness and performance of YOLOv5 and YOLOv8 in real-time human detection applications using the SEMMA (Sample, Explore, Modify, Model, and Assess) methodology also. The dataset was processed through the Roboflow platform, which facilitated both the dataset management and the labeling process. Roboflow's tools streamlined the annotation of images, ensuring consistent labeling for deep learning model training and evaluation. F1 score, recall score, and precision score are compared both YOLOv5 and YOLOv8 to evaluate the performance of these architectures. The result of the evaluations shows that the performance of the YOLOv8 is better than the YOLOv5 which, YOLOv5 achieved F1-score equal 0.5865 (58%), recall score equal 0.83 (83%), and precision score of 0.4535 (45%). Meanwhile, YOLOv8 demonstrated better performance, with F1-score of 0.7921 (79%), recall score of 0.8289 (82%), and precision score of 0.7585 (75%). Base on the evaluations, we concluded that the performance of the YOLOv8 model is greater than the YOLOv5 model for Precision, and F1-Score, while YOLOv5 has slightly better score on recall. The contribution of this study is going to implemented into Audio guidance for the blind’s prototype that have been developing in previous study.
Enhancing Smart Wheelchair Control: A Comparative Study of Optical Flow and Haar Cascade for Head Movement Muriyah, Nimatul Ma; Paerin, Paerin; Yulianto, Andik
Journal of Information System and Informatics Vol 7 No 4 (2025): December
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v7i4.1302

Abstract

The development of Artificial Intelligence, particularly in Computer Vision, has enabled real-time recognition of human movements such as head gestures, which can be utilized in smart wheelchairs for users with limited mobility. This study compares two lightweight non-deep-learning methods Lucas–Kanade Optical Flow and Haar Cascade Classifier for real-time head movement detection. Both methods were implemented in Python using OpenCV and tested in four basic directions (left, right, up, and down) under three different lighting conditions: bright, normal, and dim. Each condition consisted of 16 trials per method, resulting in a total of 96 trials. The evaluation focused on detection accuracy and decision time. Under bright lighting, Optical Flow achieved 87.5% accuracy with a decision time of 0.338-1.41 s, while Haar Cascade reached 50% accuracy with 0.616–1.20 s. Under normal lighting, Optical Flow maintained 87.5% accuracy with 0.89–1.21 s, compared to Haar Cascade’s 68.75% accuracy with 0.83–1.25 s. Under dim lighting, Optical Flow improved to 93.8% accuracy with 0.90–1.31 s, whereas Haar Cascade dropped to 62.5% accuracy with 0.89–1.58 s. These findings confirm that Optical Flow delivers more reliable and adaptive performance across varying illumination levels, making it more suitable for real-time smart wheelchair control. This study contributes to the development of affordable assistive technologies and highlights future directions for multi-user testing and hardware integration.
Co-Authors A.A. Ketut Agung Cahyawan W Abay, Margita Rahayu Adelia Anju Asmara Adelia Anju Asmara Agung Nugroho Adi, Agung Nugroho Aji Wilaksono, Aji Aldri Frinaldi Amilia Amilia Anaztasya, Azra Putri Andi Andi Andreas, Willy Anisah Hasna Jauharoh Anthony Any Juliani, Any Aripradono, Heru Wijayanto Arlina, Dilla Awaluddin Nurmiyanto, Awaluddin Billy Ardi, Billy Chandra Wijaya, Kevin Christian, Yefta Danang Wahyu Widodo Darojat, Irfa Davis Willyam, Davis Deli, Deli Delvira Jayatri Prasasti, Delvira Jayatri Dewi Wulandari Dhandhun Wacano Dilla Arlina Dion, Sandy Alferro Elvert Elvis, Elvis Erick Fernando, Nelson Hadi Hadi Haeruddin Haeruddin Herlica, Inne Herman Herto Dwi Arisyady, Herto Hervian Lanang Priyambodo, Hervian Lanang Hu dori, Hu Hudori Hudori Ikhlas, Junior Indah Purwaningsih Irawan, Ferdy Jason Jeffrey ., Jeffrey Jesson, Jesson Kevin kevin Khomali, Carlos Justin Lau, Eric Lau, Wilsen Lee, Lesley Peterson Leonardo, Kevin Lie, Melvin Lie, Steven Lim, Louis Lim, Stephani Lius, Kevin Marbun, Ricky Yohannes Marcelleno, Ng Mardya Ning Tyas Margita Rahayu Abay Marisa Handayani Maulana, Azhar Melvin, Melvin Meriana, Angelina Mistoro, Niesa Hanum Mungkap Mangapul Siahaan Muriyah, Nimatul Ma Nimatul Mamuriyah Paerin, Paerin Pelawi, Jan Putra Bahtra Agung S Pratama, Adi Nuzul Pravitasari, Vidya Ayu Prayatni Soewondo Prihat maji, Prihat Putro, Muhammad Kholif Lir Widyo Rahman, M Abdur Rahmawati, Suphia Rinaldo, Rinaldo Sabariman Sabariman Sabariman Sabariman Sak, Erwin Sama, Hendi Saputra, M. Abdilah Selina, Selina Setijawan, Wawan sherly sherly Sim, Joel Hamim Simanjuntak, Fredian Simanjuntak, Noe Prihartoyo Sopiyan, Sopiyan Stelyven, Stelyven Stephen Suphia Rahmawati Taai, Derwin Tham, Vincent Tiffano Miracle Gaghana, Dave Tjua, Selina Trianes, Agustian Utomo, Kevin Saputra Wacano, Dhandhun Wantoputri, Noviani Ima Wenky, Wenky Wilson Wilson Yeo, Stefan Yulianto P., Yulianto Yuvier, Maxi