Article Per Year (5 Year)
p-Index From 2021 - 2026
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This Author published in this journals
All Journal Journal of Electrical, Electronic, Information, and Communication Technology (JEEICT) Advance Sustainable Science, Engineering and Technology (ASSET)
Joko Hariyono
Universitas Sebelas Maret
Chemistry Computer Science & IT Control & Systems Engineering Electrical & Electronics 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.
Adaptive Cruise Control based Motor Acceleration Control using Fuzzy Logic Methods Putra Maulana Yusuf; Joko Hariyono; Joko Slamet Saputro; Agus Ramelan; Feri Adriyanto; Miftahul Anwar
Journal of Electrical, Electronic, Information, and Communication Technology Vol 5, No 2 (2023): 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.5.2.71714

Abstract

The paper presents a method for adaptive cruise control based motor acceleration control. On the long-distance driving, using vehicles that have a risk for accidents. One of these accidents is collisions between vehicles in front of them which can cause multiple collisions. With the help of the ACC feature, it can reduce the occurrence of these accidents which are caused by the driver's fatigue and weather conditions on long-distance trips. By using the Fuzzy adaptive cruise control system, it is successful in adjusting the acceleration set on the fuzzy system, and with the help of the GUI it can make it easier for the operator to set the appropriate acceleration.
Fire Detection Based on Image Using MATLAB GUI Programme Muhammad Dhafier Mu'afa; Mark Reindhard Joyakin Silalahi; Hanif Wisti Julitama; Joko Hariyono
Journal of Electrical, Electronic, Information, and Communication Technology Vol 5, No 1 (2023): 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.5.1.69091

Abstract

Computer vision-based fire detection systems overcome this limitation in that they do not identify flammability on a product-by-product basis. In this study, fire detection was carried out using the YCbCr, RGB, and HSV map approach. The offered system uses color segmentation as a component of fire detection analysis. These three colors space segments will then be extracted to determine the presence of fire in the image used. A rule which consists of five rules based on color space condition had been constructed for classification of a pixel classified as fire. If a pixel satisfies these five rules, the pixels belong to fire class.This paper consists of 6 steps, including image acquisition, image pre-processing, image segmentation, feature extraction, image classification, and GUI creation. GUI provides a visual interface that is intuitive and easy for the user to understand the proposed system. By using button and another visual elements, users can interact with the system efficiently. Based on the tests carried out, the proposed system can detect images of fire in dark and light conditions. Performance testing is done by collecting a set of fire images on the internet. Performance is judged based on how many errors are generated when detecting fire. Performance is categorized into five types, including very good, good, fair, poor, and very poor.
Co-Authors Agus Ramelan Faisal Rahutomo Feri Adriyanto Hanif Wisti Julitama Joko Slamet Saputro Mark Reindhard Joyakin Silalahi Miftahul Anwar Muhammad Dhafier Mu'afa Nanang Wiyono Putra Maulana Yusuf Rahmat Rohmani Ratih Yudhani Sutrisno Ibrahim