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All Journal Letters in Information Technology Education (LITE) Jurnal INFOTEL
Muhammad Fahmi Hidayat, Muhammad Fahmi
Unknown Affiliation
Computer Science & IT Education Electrical & Electronics Engineering

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DEVELOPMENT OF UNIVERSITY DIGITAL SKETCH-MAP BASED ON EXPERIENCES AND DIGITAL TRACES Muqorrobin, Kiroomin; Yudhistira, Moch Rajendra; Pratama, Muhammad Ardhika Mulya; Hidayat, Muhammad Fahmi; Widarto, Widarto
Letters in Information Technology Education (LITE) Vol 1, No 2 (2018)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (583.74 KB) | DOI: 10.17977/um010v1i22018p036

Abstract

The main purpose of a university is education. However, in addition to the educational process, people who are active in the university environment will surely leave valuable moments or experiences, especially in places that are often visited or even places that leave unforgettable impressions. Even so, the lack of attention to the moments or experiences makes the moments easily forgotten, and not conveyed to future generations. Therefore, we developed a digital sketch-map using past photo data and the recollections of campus society, we also conduct investigations on the recollections we got using Falk's theory of ?making of meaning? in a museum. The purpose of this study is to develop a digital sketch-map to ease archiving and saves some memories of Universitas Negeri Malang?s societ
DETEKSI OBJEK ASET RUMAH SAKIT MENGGUNAKAN COMPUTER VISION DENGAN METODE GENERATIVE ADVERSARIAL NETWORKS Suakanto, Sinung; Hidayat, Muhammad Fahmi; Hamami, Faqih; Raffei, Anis Farihan Mat; Nuryatno, Edi
JURNAL INFOTEL Vol 17 No 1 (2025): February 2025
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v17i1.1277

Abstract

Hospital asset monitoring systems encounter significant challenges in managing partially occluded medical equipment, which affects inventory management and operational efficiency. Conventional object detection methods have shown limitations in accurately detecting occluded medical equipment, potentially leading to asset management inefficiencies. This study presents an integrated framework that combines Generative Adversarial Networks (GAN) inpainting with YOLOv8 to improve the detection accuracy of partially occluded medical equipment. The proposed system was evaluated using three distinct training configurations of 500, 750, and 1000 epochs on a comprehensive medical equipment dataset. The experimental results indicate that the 1000-epoch GAN model demonstrated superior reconstruction performance, achieving a Peak Signal-to-Noise Ratio (PSNR) of 39.68 dB, Structural Similarity Index Measure (SSIM) of 0.9910, and Mean Squared Error (MSE) of 7.0030. Furthermore, the integrated YOLOv8-GAN framework maintained robust detection performance with an F1-score of 0.933, comparable to the 0.938 achieved with unoccluded original images. The detection confidence scores exhibited improvement at higher epochs, ranging from 0.824 to 0.861, suggesting enhanced performance with extended training duration. The findings demonstrate that the integration of GAN inpainting with YOLOv8 effectively enhances occluded object detection in hospital environments, offering a viable solution for improved asset monitoring systems.
Co-Authors Faqih Hamami Muqorrobin, Kiroomin Nuryatno, Edi Pratama, Muhammad Ardhika Mulya Raffei, Anis Farihan Mat Sinung Suakanto Widarto Widarto Yudhistira, Moch Rajendra