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All Journal Bulletin of Electrical Engineering and Informatics JOIV : International Journal on Informatics Visualization Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat
Seniman, Seniman
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Computer Science & IT Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Social Sciences

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Classification of Human Concentration Levels Based on Electroencephalography Signals Siregar, Baihaqi; Florence, Grace; Seniman, Seniman; Fahmi, Fahmi; Mubarakah, Naemah
JOIV : International Journal on Informatics Visualization Vol 8, No 2 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.2.2045

Abstract

Concentration denotes the capability to direct one's attention to a specific subject matter. Presently, within the era characterized by an overwhelming abundance of information inundating human existence, distractions frequently impede human concentration, thereby influencing the depth of knowledge acquisition. Various elements contribute to the decline in human concentration, including diminished metabolic states, inadequate sleep, and engaging in multiple tasks simultaneously. The cognitive state of an individual during the process of thinking can be assessed through the analysis of electroencephalography signals. The primary objective of this investigation is to facilitate experts' interpretation of electroencephalography signal outcomes for categorizing concentration levels. The dataset utilized in this examination comprises unprocessed EEG data obtained from observing individuals in both relaxation and concentration states. After data preprocessing, feature extraction is executed, and classification is performed using the Support Vector Machine technique. The outcome of this study reveals an accuracy rate of 84%. These developments allow for continual monitoring of brain function, an enhanced comprehension of cerebral activities, and increased operational efficacy of end-effectors. The implications of these advancements on prospective research opportunities are evident in the potential for more accurate diagnosis of neurological disorders and the progression of sophisticated BCI applications designed to support healthcare and monitor cognitive states. The evolution of EEG technology is paving the way for novel research pathways in neuroscience and human-computer interaction.
Bike Fitting System Based on Digital Image Processing on Road Bike Nasution, Tigor Hamonangan; Sitohang, Andreas; Seniman, Seniman; Soeharwinto, Soeharwinto
JOIV : International Journal on Informatics Visualization Vol 9, No 2 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.2.2796

Abstract

This research aims to develop a bike fitting system based on digital image processing for road bikes. The method used in this study involves using the OpenCV and MediaPipe libraries in the Python programming language to detect the rider's body pose from a video stream captured using a webcam. The body pose data is then used to calculate important angles such as elbow, hip, knee, and ankle range related to the correct riding position for road bikes. In this research, a comparison is made between the body angles obtained and the angle range considered ideal for bike fitting on road bikes. If the body angles fall within the desired range, the system will label it as "Fit”; if the body angles are outside the selected range, the system will label it as "Not Fit." The results of this study indicate that the bike fitting system based on digital image processing using a webcam can provide helpful visual feedback in improving the rider's body position for road bikes. By observing the body angles produced and seeing the "Fit" or "Not Fit" label, cyclists can adjust their position to match the ideal position in bike fitting. The system test results show a low error rate, with elbow angle having an average error of 0.81%, hip angle of 1.37%, knee angle of 0.83%, and ankle range of 1.76%. Thus, this research contributes significantly to supporting cyclists in achieving a position appropriate to their inseam height.
The implementation of the K-nearest neighbor algorithm to detect the KRSRI robot obstacles Hamonangan Nasution, Tigor; Muhammad Prihandoyo, Arza; Seniman, Seniman
Bulletin of Electrical Engineering and Informatics Vol 14, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i2.8225

Abstract

The Indonesian SAR robot contest (KRSRI) is a development of the fire extinguisher robot contest (KRPAI); initially, the robot at KRPAI only put out fires. Still, at KRSRI, the robot was asked to prioritize the SAR function. The robot had to overcome obstacles in this contest to complete it. Based on this, an obstacle detection system for the robot was designed using machine learning with the K-nearest neighbor algorithm and gray level co-occurrence matrix feature extraction. Later, the robot is expected to be able to carry out accurate obstacle detection to prioritize efficiency so that no more time is consumed due to the robot incorrectly detecting an obstacle. The results of the tests that have been carried out show that the detection accuracy based on the test dataset is 80% for rising barriers, 100% for debris obstacles, and 90% for step obstacles, and an error value of 20% for increasing obstacles is obtained, 0% for debris obstacles, and 10% for stair obstacles.
INOVASI DIGITAL DAN TEKNOLOGI UNTUK PEMBANGUNAN BERKELANJUTAN DI DESA KUTA MBELIN Efendi, Syahril; Nurahmadi, Fauzan; Manik, Fuzy Yustika; Seniman, Seniman; Harumy, T. Henny Febriana; Jaya, Ivan; Absah, Yeni; Syahputra, Muhammad Romi; Hastuti, Liana Dwi Sri; Nainggolan, Pauzi Ibrahim; Herianto, Tulus Joseph; Ginting, Dewi Sartika Br; Yudhistira, Yudhistira
Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Vol 5, No 2 (2025): Desember 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jpstm.v5i2.5154

Abstract

 Abstract: Kuta Mbelin Village in STM Hulu District, Deli Serdang Regency, utilizes digital technology to accelerate sustainable development through its official village website, kutambelin.com. This website plays a crucial role in promoting the village's potential, particularly in the agriculture and nature tourism sectors, which support the achievement of SDG 8 (Decent Work and Economic Growth). Furthermore, kutambelin.com highlights sustainable environmental management programs relevant to SDG 12 (Responsible Consumption and Production), and supports digital infrastructure innovation related to SDG 9 (Innovation, Infrastructure, and Industrialization). Keywords: Kuta Mbelin Village, digital innovation, sustainable development, SDGs, village website, local promotion, agriculture, tourism. Abstrak: Desa Kuta Mbelin di Kecamatan STM Hulu, Kabupaten Deli Serdang, memanfaatkan teknologi digital untuk mempercepat pembangunan berkelanjutan melalui situs web resmi desa, kutambelin.com. Website ini memainkan peran penting dalam mempromosikan potensi desa, khususnya di sektor pertanian dan pariwisata alam, yang mendukung pencapaian SDG 8 (Pekerjaan Layak dan Pertumbuhan Ekonomi). Selain itu, kutambelin.com menyoroti program pengelolaan lingkungan yang berkelanjutan, relevan dengan SDG 12 (Konsumsi dan Produksi yang Bertanggung Jawab), serta mendukung inovasi infrastruktur digital yang terkait dengan SDG 9 (Inovasi, Infrastruktur, dan Industrialisasi). Kata Kunci : Desa Kuta Mbelin, inovasi digital, pembangunan berkelanjutan, SDGs, website desa, promosi lokal, pertanian, pariwisata.
Co-Authors Efendi, Syahril Fahmi Fahmi Fauzan Nurahmadi Florence, Grace Fuzy Yustika Manik, Fuzy Yustika Ginting, Dewi Sartika Br Hamonangan Nasution, Tigor Harumy, T. Henny Febriana Herianto, Tulus Joseph Jaya, Ivan Muhammad Prihandoyo, Arza Naemah Mubarakah Nainggolan, Pauzi Ibrahim Nasution, Tigor Hamonangan Siregar, Baihaqi Sitohang, Andreas Soeharwinto Soeharwinto, Soeharwinto Sri Dwi Hastuti Syahputra, Muhammad Romi yeni absah Yudhistira Yudhistira