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Agus Ramelan
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Ruang Prodi Teknik Elektro Gedung 3, Lt. 2, Fakultas Teknik Universitas Sebelas Maret Jalan Ir. Sutami 36 Kentingan, Jebres, Surakarta, Jawa Tengah, Indonesia 57126
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Journal of Electrical, Electronic, Information, and Communication Technology (JEEICT)
Published by Universitas Sebelas Maret
ISSN : -     EISSN : 27151263     DOI : https://dx.doi.org/10.20961/jeeict.2.2.45291
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering
Journal of Electrical, Electronic, Information and Communication Technology (JEEICT) is a peer-reviewed open-access journal in English published twice a year by the Department of Electrical Engineering, Sebelas Maret University, Indonesia. The JEEICT aims to provide a leading-edge medium for researchers, industry professionals, engineers, educators, students to disseminate research work and studies in the fields of electrical, electronics, information and communication technology. The journal publishes work from power systems, electronics, instrumentation, and biomedical engineering, renewable energy and its application, control systems, information technology, and communication and vehicular technology disciplinary, in theoretical and experimental perspectives.
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 89 Documents
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Automated Bird Deterrent System: A Review Muhammad Fauzan Hernadi; Yusuf Haryo Timur; Roy Dongan Putra Manalu; Nabilah Khairunnisa; Diky Zakaria
Journal of Electrical, Electronic, Information, and Communication Technology Vol 7, No 1 (2025): 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.7.1.95184

Abstract

Bird pests pose a significant threat to agriculture, causing extensive crop damage and economic losses. Traditional bird repellent methods, such as scarecrows and loud noises, often lose their effectiveness over time as birds adapt. This paper reviews the development and effectiveness of an automated bird repellent system, integrating Internet of Things (IoT) and Artificial Intelligence (AI) technologies. The study used a systematic literature review (SLR) methodology, analyzing 20 articles published between 2015 and 2024. Key findings show that automated systems, utilizing sensors and AI algorithms such as YOLO, DenseNet, and Mask R-CNN, significantly improve bird detection and repellent accuracy. The DenseNet model, in particular, achieved a detection accuracy of 99.65%. The review highlights the need for further research to optimize sensor placement and assess the long-term impacts of this technology on bird behavior and agricultural ecosystems. This comprehensive review underscores the potential of automated bird repellent systems to improve crop protection and sustainability in agriculture.
Antenna Tracker System for Unmanned Aerial Vehicles: A Short Review Hayyan Yusuf; Faisal Rahutomo; Sutrisno Sutrisno
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.5.2.72496

Abstract

Unmanned Aerial Vehicle (UAV) is a modern technology used to perform difficult and dangerous aerial missions that cannot be carried out by manned aerial vehicles. Ground Control Station (GCS) is a system that manages all the parameters of the UAV. GCS and UAV communicate using radio waves through telemetry, which functions to transmit and receive flight data.  Antenna tracker is a device used to connect the GCS (Ground Control Station) and the UAV (Unmanned Aerial Vehicle). The antenna tracker works by performing tracking to direct the antenna towards the UAV. Nowadays, there are various forms of antennas used in telecommunication technology. Each type of antenna has its own radiation characteristics, some are directional, while others are more omnidirectional. Directional antennas are the right choice to be used with an antenna tracker. Generally, directional antennas have a narrow radiation range but a relatively long transmission distance. This paper provides a review of the state-of-the-art in antenna tracker technology for unmanned aerial vehicles (UAVs), with a focus on design, performance, and type of antenna. The study involved a literature search of various databases. The design approaches for antenna tracker systems range from simple single-axis trackers to sophisticated dual-axis trackers with pan-tilt mechanisms, and type of antenna such as helical were explored. The study concludes that antenna trackers have numerous applications in various industries, including military, agriculture, and surveying, and the demand for reliable and accurate antenna trackers is expected to continue to grow with the increasing popularity of UAVs.    
An Intelligent System for Traffic Monitoring and Route Optimization Using YOLOv11, Random Forest, and BCO Sukemi Sukemi; Ahmad Fali Oklilas; M. Reza Arya Pratama
Journal of Electrical, Electronic, Information, and Communication Technology Vol 7, No 2 (2025): 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.7.2.108973

Abstract

Traffic congestion is a major problem in Palembang City due to the significant growth in the number of vehicles. This study aims to develop an artificial intelligence-based system for detecting vehicle density and predicting optimal routes. Vehicle number detection is carried out using the YOLOv11 method based on CCTV data at 15 intersections in Palembang City, with training results showing an accuracy of 92%, F-1 Score of 82% and mAP@0.5 of 86.7%. In the validation and testing stages, this model achieved an accuracy of 90%, and mAP@0.5 of 81.7%. The detection data was then analyzed using the Random Forest (RF) algorithm to classify traffic conditions with a dataset of 769 rows of data, achieving an accuracy of 98.26%. Furthermore, the Bee Colony Optimization (BCO) algorithm was used to determine the fastest route by taking into account the distance traveled and the level of congestion. The results of the study show that the combination of the YOLOv11, RF, and BCO methods is able to produce an effective system in providing optimal route recommendations and helping to significantly reduce congestion. This system is expected to be a practical solution for city traffic management in the future.
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.
Development of Gemini AI as a Virtual Assistant in Student’s WhatsApp Discussion Group Ilham Alifian Firmansyah
Journal of Electrical, Electronic, Information, and Communication Technology Vol 7, No 2 (2025): 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.7.2.95453

Abstract

Introduction: WhatsApp is a social media platform that is frequently used in Indonesia. The ease of use of WhatsApp makes people of any group of age groups use it. WhatsApp also has a group feature that can be used as a discussion platform. Most students in Indonesia joined a WhatsApp group either to share information or discuss their school tasks. But not all their WhatsApp group have their teacher as a group member because sometimes they feel uncomfortable discussing something when their teacher is in the same group. So, we need a virtual assistant to help the students answer their questions while discussing. One of the most used virtual assistants is Google Gemini AI. So, researchers recommend integrating Google Gemini AI and students’ WhatsApp discussion groups. Aim of the study: To develop a virtual assistant to increase the effectiveness of students’ discussion, providing information, answering questions, or guiding them to complete their task. Method: The method used in this research development is the waterfall. Results: The Researcher successfully developed the virtual assistant and worked as planned; it answers any question when the group participant mentions it in the WhatsApp group chat room. Conclusion: The virtual assistant has a big scalability to develop; it can be trained to a specific major, depending on its group. For the next study, researchers recommend imposing a limitation so the students do not abuse their power.
Adaptive System for Streetlights in the Shopping Center Area of Purwakarta Region using Fuzzy Logic Method Dewi Indriati Hadi Putri; Hafiyyan Putra Pratama; Liptia Venica; Vormes Gema Merdeka; Makna A'raaf Kautsar
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.5.2.79675

Abstract

Streetlight systems generally use time condition as the parameter, which set the lights to be always on during specified period. This way, the system has flaws in its inefficiency and ineffectiveness. The system designed in this research considers the intensity of surrounding lights and passing pedestrians as the parameters, and fuzzy logic to get fuzzier output of the luminosity level for the streetlight. From the results of testing and analysis, it can be concluded that the design in this research has been successfully built as the results obtained are in accordance with the previously set fuzzy logic universe of discourse. By implementing an adaptive street lighting system in this study can help streamline light energy, because the street lighting lights can adjust themselves depending on the presence or absence of pedestrians passing by using a PIR sensor and the level of light brightness in that place using an LDR sensor.
A Literature Review: Bearing Fault in BLDC Motor Based on Vibration and Thermal Signals Meiyanto Eko Sulistyo; Didik Djoko Susilo; Muhammad Nizam; Ubaidillah Ubaidillah
Journal of Electrical, Electronic, Information, and Communication Technology Vol 7, No 1 (2025): 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.7.1.100165

Abstract

This review of the literature looks into the use of vibration and thermal signals for the diagnosis and detection of bearing problems in brushless DC (BLDC) motors. The study highlights the efficacy of current developments in diagnostic algorithms and signal processing approaches in detecting bearing irregularities. The comparative study of vibration and heat monitoring techniques is highlighted, along with a discussion of each method's benefits and drawbacks. The integration of various methods for improved fault detection accuracy is also examined in the paper. The results indicate that a hybrid strategy that combines temperature analysis and vibration provides a reliable way to identify BLDC motor problems early on, which could enhance maintenance plans and operational dependability.
Implementation of Cellular-Based Drone Module using Cloud Services Adrian Ferdinand Jotham; Fussy Mentari Dirgantara; Muhammad Faris Ruriawan
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.5.2.72640

Abstract

The notion of a smart city incorporates the integration of infrastructure, services, and the community and encompasses the deployment of unmanned aerial vehicles (UAVs) for monitoring crop fields, facilitating logistics delivery, and performing high-altitude cleaning tasks. In a smart city, the interconnectedness of devices is realized through the medium of the Internet of Things (IoT). This research endeavors to explore the usage of Beyond Visual Line of Sight (BVLOS) for enabling remote command and control of UAV/UGV modes, leveraging 4G/LTE connectivity as an enabler. 4G/LTE connectivity is known for its improvement in data transfer speed and network capacity, which potentially enables the connection of more devices, including drones. The high availability and scalability of cloud services have become crucial factors in utilizing cloud services as the most cost-effective and expedient relay for connecting two nodes over the internet globally for now. The proposed methodology would be integrated into a smart drone module, which would be deployed at a small scale as a component of the Intelligent Transportation System (ITS).
Enhancing Face Detection Performance in Low-Light Conditions Using NIR Thermal Imaging and Image Morphology Maulisa Oktiana; Cut Salsabilla Azra; Rusdha Muharar; Fajrul Islamy; Rizka Ramadhana; Melinda Melinda; Niza Aulia; Muharratul Mina Rizky; Maya Fitria
Journal of Electrical, Electronic, Information, and Communication Technology Vol 7, No 2 (2025): 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.7.2.108786

Abstract

Face detection plays a vital role in biometric, security, and surveillance systems. Conventional approaches based on the visible light (VIS) spectrum often suffer performance degradation under poor lighting conditions, limiting their reliability. To address this issue, this study employs thermal imagery in the Near-Infrared (NIR) spectrum, which is less affected by ambient light, combined with image morphology operations to enhance segmentation accuracy. Experiments were conducted using the LDHF-DB dataset (300 images at distances of 1 m, 60 m, and 100 m) and a subset of the Tuft dataset (60 images). Face detection was performed using the HOG + SVM method, followed by Otsu thresholding and morphological operations. Performance was evaluated using Peak Signal-to-Noise Ratio (PSNR). Results show that applying morphological operations significantly improves PSNR values, with an average increase of more than 35%. The best performance was achieved on the 1 m subset, while longer distances presented greater challenges. These findings highlight the potential of integrating NIR thermal imagery and morphological processing to improve the robustness and reliability of face detection systems in low-light environments.

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