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Journal : international journal of electrical and computer engineering

Development of a solar radiation sensor system with pyranometer Muchamad Rizky Nugraha; Andi Adriansyah
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i2.pp1385-1391

Abstract

Solar energy is a result of the nuclear fusion process in the form of a series of thermonuclear events that occur in the Sun's core. Solar radiation has a significant impact on the lives of all living things on earth. The uses, as mentioned earlier, are when the solar radiation received requires a certain amount and vice versa. As a result, a more accurate instrument of solar radiation is required. A specific instrument is typically used to measure solar radiation parameters. There are four solar radiation parameters: diffusion radiation, global radiation, direct radiation, and solar radiation duration. Thus, it needs to use many devices to measure radiation data. The paper designs to measure all four-radiation data by pyranometer with particular modification and shading device. This design results have a high correlation with a global standard with a value of R=0.73, diffusion with a value of R=0.60 and a sufficiently strong direct correlation with a value of R=0.56. It can be said that the system is much simpler, making it easier to monitor and log the various solar radiation parameters.
Response time optimization for vulnerability management system by combining the benchmarking and scenario planning models Arif Basuki; Andi Adriansyah
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i1.pp561-570

Abstract

The growth of information and communication technology has made the internet network have many users. On the other side, this increases cybercrime and its risks. One of the main attack targets is network weakness. Therefore, cyber security is required, which first does a network scan to stop the attack. Points of vulnerability on the network can be discovered using scanning techniques. Furthermore, mitigation or recovery measures can be implemented. However, it needs a short response time and high accuracy while scanning to reduce the level of damage caused by cyber-attacks. In this paper, the proposed method improves the performance of a vulnerability management system based on network and port scanning by combining the benchmarking and scenario planning models. On a network scanning to discover open ports on a subnet, Masscan can achieve response times of less than 2 seconds, and on scenario planning for detection on a single host by Nmap can reach less than 4 seconds. It was combining both models obtained an adequate optimization response time. The total response time is less than 6 seconds.
Object detection in printed circuit board quality control: comparing algorithms faster region-based convolutional neural networks and YOLOv8 Kustija, Jaja; Fahrizal, Diki; Nasir, Muhamad; Adriansyah, Andi; Muttaqin, Muhammad Husni
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i3.pp2796-2808

Abstract

Along with the development of electronic technology, the integration of numerous components on printed circuit board (PCB) boards has resulted in increasingly complex and intricate layouts. Small defects in traces can lead to failures in electronic functions, making the inspection of PCB surface layouts a critical process in quality control. Given the limitations of manual inspection, which struggles to detect such defects due to their size and complexity, there is a growing need for a PCB inspection system that utilizes automated optical inspection (AOI) based on deep learning detection. This research develops and compares two deep learning algorithms, faster region-based convolutional neural networks (R-CNN) and YOLOv8, to identify the most effective algorithm for detecting defects on PCB layouts. The findings of this study indicate that the YOLOv8 algorithm outperforms faster R-CNN, with the YOLOv8x variant emerging as the best model for defect detection. The YOLOv8x model achieved performance scores of 0.962 (mAP@50), 0.503 (mAP@50:95), 0.953 (Precision), 0.945 (Recall), and 0.949 (F1-score). These results provide a strong foundation for further research into the application of AOI for PCB defect detection and other quality control processes in manufacturing, using optimized deep learning models.
Co-Authors Ab Ghani, Muhammad Amin Abdi Wahab Abdul Mutalib Leman Abdurohman Abdurohman ABU UBAIDAH SHAMSUDIN Abu Ubaidah Shamsudin Adikrisna Nugraha Akhmad Wahyu Dani Amrullah , Ahmad Ghozali Annisa Hakim Zamzami Arif Basuki Badaruddin . Badaruddin Badaruddin Cak Fangky Poernomo Chenwei Deng Dafit Feriyanto Deng, Chenwei Dodi Hermawan Eko Ihsanto Elly Yuliawati Erna Setiany Fahrizal, Diki Fengfeng Xi Ferdana, Nanda Firdaus, Ade Furqan Furqan Guangjie Yuan Hadi Pranoto Hadi Pranoto Haekal, Jakfat Heri Hermawan Hitimana, Sabin Hutomo, Fajri Rezki Jaja Kustija, Jaja Julpri Andika Kasmad Ariansyah KOERNIAWAN, SETYA DWI Long Li Md Nor, Danial Mirzanu Rizki GM Mirzanu Rizki GM Mochamad Irlan Malik Mohamed Nasir, Noorhamizah Muchamad Rizky Nugraha Mudrik Alaydrus Muhamad Nasir, Muhamad Muhammad Hafizd Ibnu Hajar Muhammad Hanif Budiutomo Muhammad Yusuf Muthia Rahayu Muttaqin, Muhammad Husni Oka Hidyatama Pratiwi, Riri Putri Wulandari RAHAYU, FAJAR Rama Sulistyawan Ramadhan, Kurnia Reni Ika Andriani Ri zally Priatmadja Rino Ferdian Surakusumah Rio Mubarak Rizal Bahaweres Rizal Bahaweres Rizki Briandana Rizky Dinata Robi Yusuf Habibie Sabin Hitimana Said Attamimi Selomah, Mohammad Suhaimi Setiyo Budiyanto Setya Dwi Koerniawan Shamsudin H. Mohd. Amin Shamsudin, Abu Ubaidah Shamsudin, Abu Ubaidillah Suhartina, Rahmalisa Supaat Zakaria Suwoyo, Heru Tay, Tay Gaik Thong, Zhou Tian, Yingzhong Tian, Yingzhong Tjetjep Rony Budiman Tjetjep Rony Budiman Tong Zhou Triwidya Mochtar, Thathit Gumilar Wenbin Wang Wijaya Wijaya Yananto Mihadi Putra Yanti Yanti Yifan Li Yingzhong Tian Yingzhong Tian Yudhi Gunardi Yuliza . Yuliza Yuliza Zakaria, Supaat Zendi Iklima Zhou Thong ZULHAMIDI, ZULHAMIDI Zulkifli, Muhammad Fathi Yakan