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All Journal Bulletin of Electrical Engineering and Informatics Abdimas Buletin Ilmiah Sarjana Teknik Elektro Journal of Robotics and Control (JRC) INTEGRITAS : Jurnal Pengabdian International Journal of Robotics and Control Systems Automotive Experiences Journal of Fuzzy Systems and Control (JFSC)
Maghfiroh, Hari
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mechanical Engineering Social Sciences

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Journal : Journal of Robotics and Control (JRC)

 1 
Online Navigation of Self-Balancing Robot using Gazebo and RVIZ Maghfiroh, Hari; Probo Santoso, Henry
Journal of Robotics and Control (JRC) Vol 2, No 5 (2021): September (Forthcoming Issue)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Human activity has been increasing, to support the activity, people in the modern era create robots to replace some human activities. The interest in two-wheeled balance robots has continued to increase, this is because it is highly maneuverable, making it efficient for use in various areas. In this study, the online navigation of a two-wheeled self-balancing robot is done. The connection between the robot and online navigation is using a Wi-Fi connection. The world model base on the real room is created by Gazebo and then visualized in RVIZ. The map creation and navigation process are handled by the package provided by ROS. The results of the simulation and real tracking show that the robot can move from the starting point to the destination point in either a straight or a curved path. The difference of the final position of the robot between simulation and real tracking is only (15.4 cm, 4 cm) and (9.6 cm, 43 cm) for the straight and curved path. This result proved that online navigation can be used to navigate an autonomous robot without real navigation sensors.
Speed Control of Induction Motor using LQG Maghfiroh, Hari; Iftadi, Irwan; Sujono, Augustinus
Journal of Robotics and Control (JRC) Vol 2, No 6 (2021): November
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.26138

Abstract

The electric motor is one of the technological developments which can support the production process. Not only in the manufacturing, but also in the transportation sector. The AC motor is divided into the synchronous and asynchronous motor. One type of asynchronous motor which widely used is the induction motor. In this study, the application of the IFOC control method and the LQG speed control method will be used to control the speed of an induction motor. The PID algorithm is also used as a comparison. Tests were carried out using MATLAB software. The speed variation and load variation are tested to validate the controller performance. PID is superior in terms of settling time and IAE. On the other hand, LQG is better in energy consumption. In terms of IAE, LQG has a higher value compared to PID by up to 56.67%. On the other hand, LQG is superior in terms of energy, which is 8.38% more efficient.
Advancements, Challenges and Safety Implications of AI in Autonomous Vehicles: A Comparative Analysis of Urban vs. Highway Environments Abu, N. S.; Bukhari, W. M.; Adli, M. H.; Maghfiroh, Hari; Ma’arif, Alfian
Journal of Robotics and Control (JRC) Vol 5, No 3 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i3.21114

Abstract

This research reviews AI integration in AVs, evaluating its effectiveness in urban and highway settings. Analyzing over 161 studies, it explores advancements like machine learning perception, sensor technology, V2X communication, and adaptive cruise control. It also examines challenges like traffic congestion, pedestrian and cyclist safety, regulations, and technology limitations. Safety considerations include human-AI interaction, cybersecurity, and liability/ethics. The study contributes valuable insights into the latest developments and challenges of AI in AVs, specifically in urban and highway contexts, which will guide future transportation research and decision-making. In urban settings, AI-powered sensor fusion technology helps AVs navigate dynamic traffic safely. On highways, adaptive cruise control systems maintain safe distances, reducing accidents. These findings suggest AI facilitates safer navigation in urban areas and enhances safety and efficiency on highways. While AI integration in AVs holds immense potential, innovative solutions like advanced perception systems and optimized long-range communication are needed to create safer and more sustainable transportation systems.
Application of Sentiment Analysis as an Innovative Approach to Policy Making: A review Firdaus, Asno Azzawagama; Saputro, Joko Slamet; Anwar, Miftahul; Adriyanto, Feri; Maghfiroh, Hari; Ma'arif, Alfian; Syuhada, Fahmi; Hidayat, Rahmad
Journal of Robotics and Control (JRC) Vol 5, No 6 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i6.22573

Abstract

This literature review comprehensively explains the role of sentiment analysis as a policymaking solution in companies, organizations, and individuals. The issue at hand is how sentiment analysis can be effectively applied in decision making. The solution is to integrate sentiment analysis with the latest NLP trends. The contribution of this research is the assessment of 100-200 recent studies in the period 2020-2024 with a sample of more than 5,000 data, as well as the impact of the resulting policy recommendations. The methods used include evaluation of techniques such as Deep Learning, lexicon-based, and Machine Learning, using evaluation matrices such as F1-score, precision, recall, and accuracy. The results showed that Deep Learning techniques achieved an average accuracy of 93.04%, followed by lexicon-based approaches with 88.3% accuracy and Machine Learning with 83.58% accuracy. The findings also highlight the importance of data privacy and algorithmic bias in supporting more responsive and data-driven policymaking. In conclusion, sentiment analysis is reliable in areas such as e-commerce, healthcare, education, and social media for policy-making recommendations. However, special attention should be paid to challenges such as language differences, data bias, and context ambiguity which can be addressed with models such as mBERT, model auditing, and proper tokenization.
Application of Sentiment Analysis as an Innovative Approach to Policy Making: A review Firdaus, Asno Azzawagama; Saputro, Joko Slamet; Anwar, Miftahul; Adriyanto, Feri; Maghfiroh, Hari; Ma'arif, Alfian; Syuhada, Fahmi; Hidayat, Rahmad
Journal of Robotics and Control (JRC) Vol. 5 No. 6 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i6.22573

Abstract

This literature review comprehensively explains the role of sentiment analysis as a policymaking solution in companies, organizations, and individuals. The issue at hand is how sentiment analysis can be effectively applied in decision making. The solution is to integrate sentiment analysis with the latest NLP trends. The contribution of this research is the assessment of 100-200 recent studies in the period 2020-2024 with a sample of more than 5,000 data, as well as the impact of the resulting policy recommendations. The methods used include evaluation of techniques such as Deep Learning, lexicon-based, and Machine Learning, using evaluation matrices such as F1-score, precision, recall, and accuracy. The results showed that Deep Learning techniques achieved an average accuracy of 93.04%, followed by lexicon-based approaches with 88.3% accuracy and Machine Learning with 83.58% accuracy. The findings also highlight the importance of data privacy and algorithmic bias in supporting more responsive and data-driven policymaking. In conclusion, sentiment analysis is reliable in areas such as e-commerce, healthcare, education, and social media for policy-making recommendations. However, special attention should be paid to challenges such as language differences, data bias, and context ambiguity which can be addressed with models such as mBERT, model auditing, and proper tokenization.
Concerns of Ethical and Privacy in the Rapid Advancement of Artificial Intelligence: Directions, Challenges, and Solutions Furizal, Furizal; Ramelan, Agus; Adriyanto, Feri; Maghfiroh, Hari; Ma'arif, Alfian; Kariyamin, Kariyamin; Masitha, Alya; Fawait, Aldi Bastiatul
Journal of Robotics and Control (JRC) Vol. 5 No. 6 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i6.24090

Abstract

AI is a transformative technology that emulates human cognitive abilities and processes large volumes of data to offer efficient solutions across various sectors of life. Although AI significantly enhances efficiency in many areas, it also presents substantial challenges, particularly regarding ethics and user privacy. These challenges are exacerbated by the inadequacy of global regulations, which may lead to potential abuse and privacy violations. This study provides an in-depth review of current AI applications, identifies future needs, and addresses emerging ethical and privacy issues. The research explores the important roles of AI technologies, including multimodal AI, natural language processing, generative AI, and deepfakes. While these technologies have the potential to revolutionize industries such as content creation and digital interactions, they also face significant privacy and ethical challenges, including the risks of deepfake abuse and the need for improved data protection through platforms like PrivAI. The study emphasizes the necessity for stricter regulations and global efforts to ensure ethical AI use and effective privacy protection. By conducting a comprehensive literature review, this research aims to provide a clear perspective on the future direction of AI and propose strategies to overcome barriers in ethical and privacy practices.
Co-Authors Abu, N. S. Adha Imam Cahyadi Adli, M. H. Adriyanto, Feri Ahmad Baballe , Muhammad Al Madani Kurniawan, Aqsha Aldi Bastiatul Fawait Fawait Alfian Ma’arif ALYA MASITHA Anif Jamaluddin Anwar, Miftahul Apribowo, Chico Hermanu Brillianto Asno Azzawagama Firdaus Baballe, Muhammad Ahmad Bizuayehu, Getenesh Melie Bukhari, W. M. Chekol, Yenework Belayneh Dwi Ana Ratna Wati Esa Apriaskar Fahmi Syuhada Fahmizal Fahmizal, Fahmizal Fatimawardhani, Sekar Furizal, Furizal Geonoky Hanifah Rahmi Fajrin, Hanifah Rahmi Hermanu, Chico Inayati Inayati Irwan Irwan Joko Slamet Saputro Juliatama, Hanif Wisti Kariyamin, Kariyamin Lambang GH, R.Lulus Lora Khaula Amifia Meiyanto Eko Sulistyo Mekonnen, Atinkut Molla Moch. Iskandar Riansyah Muhammad Nizam Munaye, Yirga Yayeh Nia Maharani Raharja Oyas Wahyunggoro Probo Santoso, Henry Putra, Mufti Reza Aulia Ramelan, Agus Sitorini Zul Hizmi, Vernanda Sujono, Augustinus Surriani, Atikah Suwarno, Iswanto Syuhada, Fahmi Trio Putra, Jimmy Winda, Wiwik Nur