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All Journal Journal of Electrical, Electronic, Information, and Communication Technology (JEEICT) Journal of Fuzzy Systems and Control (JFSC) Advance Sustainable Science, Engineering and Technology (ASSET)
Sutrisno Ibrahim
Universitas Sebelas Maret
Chemistry Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering

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Optimization of Tracking Algorithm on Mouse Movement Monitoring Platform in Medical Testing Sutrisno Ibrahim; Rahmat Rohmani; Joko Hariyono; Faisal Rahutomo; Nanang Wiyono; Ratih Yudhani
Advance Sustainable Science Engineering and Technology Vol. 8 No. 3 (2026): May - July
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i3.2879

Abstract

Accurate monitoring of mouse behavior in the Elevated Plus Maze (EPM) is essential for anxiety-related biomedical research, yet manual observation is time-consuming, subjective, and prone to human error. This study proposes an optimized automated tracking framework that integrates YOLOv8 detection with tracking methods including an adaptive Kalman Filter and DeepSORT, and compares them with conventional trackers such as CSRT and GOTURN. System performance was evaluated using Intersection over Union (IoU), Center Location Error (CLE), and Frames Per Second (FPS), with the Weighted Scoring Method (WSM) used for overall performance comparison. Experimental results show that the proposed YOLOv8 with adaptive Kalman filtering (frame interval = 5) provides the best balance between accuracy and computational efficiency. The approach achieved an IoU of 0.89 and CLE of 2.34 while increasing processing speed from 10.44 FPS to 22.55 FPS, representing an improvement of approximately 116% compared with the baseline configuration. Despite a slight increase in failure rates, the framework maintained stable real-time tracking performance under laboratory conditions. These results demonstrate that the proposed system improves both tracking efficiency and robustness, offering a reliable automated solution for high-throughput behavioral monitoring. The framework is particularly suitable for laboratory automation environments, supporting more objective behavioral assessment and improved data integrity in preclinical biomedical research.
Implementation of Object Detection Method for Intelligent Surveillance Systems at the Faculty of Engineering, Universitas Sebelas Maret (UNS) Surakarta Aris Maulana Fauzan; Sutrisno Ibrahim; Meiyanto Eko Sulistyo
Journal of Electrical, Electronic, Information, and Communication Technology Vol 4, No 1 (2022): JOURNAL OF ELECTRICAL, ELECTRONIC, INFORMATION, AND COMMUNICATION TECHNOLOGY
Publisher : Universitas Sebelas Maret (UNS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/jeeict.4.1.61197

Abstract

The number of positive Covid-19 cases in Indonesia continue to increase. This increase influenced by the behavior of Indonesian citizens in dealing with the pandemic, one of which is rarely wearing masks. In this study, we implemented an object detection method for intelligent surveillance systems (ISS) at the Faculty of Engineering, Universitas Sebelas Maret (UNS), Surakarta. By implementing face detection and mask detection, the surveillance system can recognize whether a person in a CCTV video frame is wearing a mask or not. In addition, deep metric learning and histogram of gradient (HOG) are applied to recognize faces of unmasked people in images. The test results show that the surveillance system can recognize the use of masks with 75%-87% accuracy rate. Furthermore, the accuracy rate for facial recognition on images ranges from 69% -100% for each person
AR-NAVIS: Mobility Application for Blind and Deaf Students Based on Augmented Reality Joko Slamet Saputro; Gunardi Gunardi; Fadjri Kirana Anggarani; Najya Anastasya; Reva Setiabudi; Sutrisno Ibrahim
Journal of Electrical, Electronic, Information, and Communication Technology Vol 6, No 1 (2024): JOURNAL OF ELECTRICAL, ELECTRONIC, INFORMATION, AND COMMUNICATION TECHNOLOGY
Publisher : Universitas Sebelas Maret (UNS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/jeeict.6.1.85475

Abstract

Students with disabilities, especially those with visual and hearing impairments, face challenges in navigating through the campus environment. Hence, the development of AR-NAVIS as an Augmented Reality (AR)-based mobility orientation application stands as a significant innovation in providing services for them. This application aims to assist disabled students in moving within the campus environment, both indoors and outdoors. AR-NAVIS identifies the safest and most efficient routes, enabling disabled students to engage in independent activities and enhancing both their academic and non-academic performance. The application development process involves analyzing students' needs, prototype design, model validation, trials, and dissemination. Its features include AR-based 3D guidance, directional text, voice, vibration mode, and hazard information. The app is expected to provide accurate information about buildings or locations that are the destination for disabilities students. The result show that application development can guide disabilities user move between buildings smoothly. The experiment found that there was an increase in student activity after having this application.
Image Processing-Based Morris Water Maze Rat Tracking System: Design and Analysis Sutrisno Ibrahim; Gayatri Dewani; Joko Hariyono; Faisal Rahutomo; Nanang Wiyono; Ratih Yudhani
Journal of Fuzzy Systems and Control Vol. 4 No. 3 (2026): Vol. 4 No. 3 2026
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v4i3.411

Abstract

Four experimental rats consisting of one normal rat and three Alzheimer's-induced rats were analyzed. The proposed system employed ImageJ integrated with the RatsTrack and Macro RatsTrack plugins using a centroid based tracking approach. The system successfully extracted movement trajectories, distance travelled, speed, acceleration, and quadrant dwell time during acquisition and probe trials. The system performance was validated by comparing quadrant dwell times obtained from the proposed system with manual observations. The percentage differences ranged from 2.29% to 70.97%. demonstrating that the proposed system can effectively represent rat behavioral patterns, although discrepancies remain in certain quadrants requiring further refinement.
Co-Authors Aris Maulana Fauzan Fadjri Kirana Anggarani Faisal Rahutomo Gayatri Dewani Gunardi Gunardi Joko Hariyono Joko Slamet Saputro Meiyanto Eko Sulistyo Najya Anastasya Nanang Wiyono Rahmat Rohmani Ratih Yudhani Reva Setiabudi