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All Journal TEKNIK Jurnal Pendidikan Teknologi dan Kejuruan Indonesian Journal of Electrical Engineering and Informatics (IJEEI) ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika JOIV : International Journal on Informatics Visualization JST ( Jurnal Sains Terapan ) JURNAL INTEGRASI JOURNAL OF APPLIED INFORMATICS AND COMPUTING J-Dinamika: Jurnal Pengabdian Kepada Masyarakat JEECAE (Journal of Electrical, Electronics, Control, and Automotive Engineering) Jurnal Teknik Mesin dan Mekatronika (Journal of Mechanical Engineering and Mechatronics) MATRIX : JURNAL MANAJEMEN TEKNOLOGI DAN INFORMATIKA Jurnal Rekayasa elektrika
Hary Oktavianto
Departemen Teknik Elektro, Politeknik Elektronika Negeri Surabaya
Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Social Sciences Transportation Other

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Journal : Jurnal Rekayasa elektrika

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Improved Performance of Trash Detection and Human Target Detection Systems using Robot Operating System (ROS) Kisron Kisron; Bima Sena Bayu Dewantara; Hary Oktavianto
Jurnal Rekayasa Elektrika Vol 17, No 2 (2021)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1282.865 KB) | DOI: 10.17529/jre.v17i2.20805

Abstract

In a visual-based real detection system using computer vision, the most important thing that must be considered is the computation time. In general, a detection system has a heavy algorithm that puts a strain on the performance of a computer system, especially if the computer has to handle two or more different detection processes. This paper presents an effort to improve the performance of the trash detection system and the target partner detection system of a trash bin robot with social interaction capabilities. The trash detection system uses a combination of the Haar Cascade algorithm, Histogram of Oriented Gradient (HOG) and Gray-Level Coocurrence Matrix (GLCM). Meanwhile, the target partner detection system uses a combination of Depth and Histogram of Oriented Gradient (HOG) algorithms. Robotic Operating System (ROS) is used to make each system in separate modules which aim to utilize all available computer system resources while reducing computation time. As a result, the performance obtained by using the ROS platform is a trash detection system capable of running at a speed of 7.003 fps. Meanwhile, the human target detection system is capable of running at a speed of 8,515 fps. In line with the increase in fps, the accuracy also increases to 77%, precision increases to 87,80%, recall increases to 82,75%, and F1-score increases to 85,20% in trash detection, and the human target detection system has also improved accuracy to 81%, %, precision increases to 91,46%, recall increases to 86,20%, and F1-score increases to 88,42%.
Improved Performance of Trash Detection and Human Target Detection Systems using Robot Operating System (ROS) Kisron Kisron; Bima Sena Bayu Dewantara; Hary Oktavianto
Jurnal Rekayasa Elektrika Vol 17, No 2 (2021)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v17i2.20805

Abstract

In a visual-based real detection system using computer vision, the most important thing that must be considered is the computation time. In general, a detection system has a heavy algorithm that puts a strain on the performance of a computer system, especially if the computer has to handle two or more different detection processes. This paper presents an effort to improve the performance of the trash detection system and the target partner detection system of a trash bin robot with social interaction capabilities. The trash detection system uses a combination of the Haar Cascade algorithm, Histogram of Oriented Gradient (HOG) and Gray-Level Coocurrence Matrix (GLCM). Meanwhile, the target partner detection system uses a combination of Depth and Histogram of Oriented Gradient (HOG) algorithms. Robotic Operating System (ROS) is used to make each system in separate modules which aim to utilize all available computer system resources while reducing computation time. As a result, the performance obtained by using the ROS platform is a trash detection system capable of running at a speed of 7.003 fps. Meanwhile, the human target detection system is capable of running at a speed of 8,515 fps. In line with the increase in fps, the accuracy also increases to 77%, precision increases to 87,80%, recall increases to 82,75%, and F1-score increases to 85,20% in trash detection, and the human target detection system has also improved accuracy to 81%, %, precision increases to 91,46%, recall increases to 86,20%, and F1-score increases to 88,42%.
LoRa-Based IoT Recommendations for Surabaya City Drainage Channel Using Multi-Node Multi-Hop Communication Izzulhaq, Muhammad Arya; Widodo, Rusminto Tjatur; Oktavianto, Hary
Jurnal Rekayasa Elektrika Vol 21, No 2 (2025)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v21i2.45095

Abstract

This paper focuses on the development of a multi-hop LoRa (Long-Range) communication network for real-time monitoring of urban drainage Internet of Things (IoT), specifically simulating the flood-prone area along the drainage channel of Jalan Jawa, Surabaya City. The novelty of this research lies in the selection of the optimal communication environment through path loss and shadowing analysis prior to implementing a multi-node, multi-hop, sensor medium access control (S-MAC) method. The selected environment at the first location demonstrated a lower path loss exponent of 1.55, typical of "in-building line-of-sight," compared to the second location with a loss exponent of 2.82, which resembled "urban area cellular radio." Applying the multi-hop technique successfully extended the data transmission range up to 750 meters with nodes placed at 250 meter intervals while maintaining a high data transfer rate. The experiments showed that increasing distance significantly reduced the received signal strength indicator (RSSI), with values dropping from -52.75 dBm at 150 meters to -98.25 dBm at 750 meters. This paper demonstrates the feasibility of using multi-hop communication rather than the conventional multi-node technique to ensure reliable data transmission and wider range, offering a solid foundation for building a robust communication network in urban drainage monitoring systems.
Co-Authors Abdillah Aziz Muntashir Abdullah Aziz Muntashir Achmad Purnomo Wijaya Amang Sudarsono, Amang angga wahyu aditya Apriyanto, R. Akbar Nur APRIYANTO, RADEN AKBAR NUR Aulia, Fira Bagus Nugraha Deby Ariyadi Bambang Sumantri BASUKI, GAMAR Bima Sena Bayu Dewantara Dadet Pramadihanto Era Purwanto Fakhruddin, Hanif Hasyier Fatekha, Rifqi Amalya GAMAR BASUKI Gamar Basuki Gigih Prabowo Handri Toar HANIF HASYIER FAKHRUDDIN Hanif Hasyier Fakhruddin Hendriawan, Akhmad Idris Winarno Ilahi, Ahmada Haiz Zakiyil Irwansyah, Arif Izzulhaq, Muhammad Arya Kadek Reda Setiawan Suda Kisron Kisron M Udin Harun Al Rasyid, M Udin Harun Mentari Putri Jati MOCHAMAD ARI BAGUS NUGROHO Niam Tamami R. Akbar Nur Apriyanto R. Akbar Nur Apriyanto R. Akbar Nur Apriyanto R. Oktav Yama Hendra Ramadhan, Ibnu Cipta Ridwan Ridwan Rusli, Muhammad Rizani Rusminto Tjatur Widodo Setiawan Suda, Kadek Reda Sri Muntiah Andriami Wahjoe Tjatur Sesulihatien Wirama, I Made Adiswara