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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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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.
Adaptive Fuzzy-PI for Induction Motor Speed Control Maghfiroh, Hari; Slamet Saputro , Joko; Fahmizal, Fahmizal; Ahmad Baballe , Muhammad
Journal of Fuzzy Systems and Control Vol. 1 No. 1 (2023): Vol. 1, No. 1, 2023
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v1i1.24

Abstract

An induction motor (IM) is one type of AC motor which widely used. IM is chosen due to its simplicity, reliability, efficiency, and low cost. There are many methods proposed to control the speed of IM which is known as variable speed drive (VFD). In this study, the DTC method is used since it is more robust to the parameter’s changes. The combination of the Fuzzy and PI method is used in speed control. PID performances decrease when the system condition changes. Therefore, fuzzy is used as an adaptive algorithm to vary the PID gain. It was superior in terms of settling time, overshoot/ undershoot, and IAE compared to the PI method. It has lower IAE in both speed tracking and loaded conditions by 44.98% and 4.47%, respectively.
Hydraulic Power System Control using State Feedback Controller (SFC) Fahmizal; Trio Putra, Jimmy; Fatimawardhani, Sekar; Maghfiroh, Hari
Journal of Fuzzy Systems and Control Vol. 1 No. 1 (2023): Vol. 1, No. 1, 2023
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v1i1.30

Abstract

In an electrical network, generators work and provide power to the loads. When the load on the generator increases, the speed of the generator decreases then resulting in a reduction in the frequency of the network. This paper was designed within the state feedback controller (SFC) to improve the hydraulic power system performance. The performance of the proposed controller is compared with simple feedback controller (FC) in the simulation environment. The load variation was tested which is 5%, 10%, and 20% variation. The testing results show that in terms of steady state error (SSE) and overshoot, the SFC is superior. In terms of settling time, the FC method is faster. Since it quickly reaches steady event not getting into set-point. The overall, it can be concluded that SFC can give better performance than FC in the frequency control of a hydraulic power system.
Rotary Inverted Pendulum Control with Pole Placement Fahmizal; Geonoky; Maghfiroh, Hari
Journal of Fuzzy Systems and Control Vol. 1 No. 3 (2023): Vol. 1, No. 3, 2023
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v1i3.152

Abstract

The inverted pendulums are multivariable and highly unstable dynamic systems. The inverted pendulum has been used to answer many modern control and control system designs because it has several problems relating to the system model of nonlinearity, difficulty, and inactivity. In this research, the main topic is the rotatory inverted pendulum. Circular path to eliminate the path that is on the pendulum that is traversed by the transversal path. In this paper, the Inverted Rotatory Pendulum is analyzed by state feedback which is adjusted by pole placement. The result of design selection in the system is very important to pay attention to the area where the pendulum will reach the point of agreement.
Discount Factor Parametrization for Deep Reinforcement Learning for Inverted Pendulum Swing-up Control Surriani, Atikah; Maghfiroh, Hari; Wahyunggoro, Oyas; Cahyadi, Adha Imam; Fajrin, Hanifah Rahmi
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 1 (2025): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i1.10268

Abstract

This study explores the application of deep reinforcement learning (DRL) to solve the control problem of a single swing-up inverted pendulum. The primary focus is on investigating the impact of discount factor parameterization within the DRL framework. Specifically, the Deep Deterministic Policy Gradient (DDPG) algorithm is employed due to its effectiveness in handling continuous action spaces. A range of discount factor values is tested to evaluate their influence on training performance and stability. The results indicate that a discount factor of 0.99 yields the best overall performance, enabling the DDPG agent to successfully learn a stable swing-up strategy and maximize cumulative rewards. These findings highlight the critical role of the discount factor in DRL-based control systems and offer insights for optimizing learning performance in similar nonlinear control problems.
Induction Motor Speed Control Using PID Tuned by Particle Swarm Optimization Under Vector Control Maghfiroh, Hari; Sulistyo, Meiyanto Eko; Ma’arif, Alfian; Raharja, Nia Maharani; Suwarno, Iswanto; Wati, Dwi Ana Ratna; Baballe, Muhammad Ahmad
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 2 (2025): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i2.13112

Abstract

Induction motors (IMs) are widely used in industrial applications due to their cost-effectiveness, durability, and low maintenance requirements. This study investigates the speed control of an induction motor using vector control combined with a PID controller whose parameters are tuned via Particle Swarm Optimization (PID-PSO). A reduced-order small-signal state-space model is derived from a detailed nonlinear IM model to facilitate efficient controller tuning while maintaining fidelity to real-world behavior. The PID parameters are optimized using PSO, with the Integral of Absolute Error (IAE) selected as the objective function due to its ability to penalize long-duration deviations and reflect steady-state performance. The optimized PID controller is then validated on the full nonlinear IM model under speed and load variations. Simulation results demonstrate that PID-PSO significantly outperforms manually tuned PID control in terms of tracking accuracy, reducing IAE by 37.79% and 14.76% under speed and load variation conditions, respectively. However, this improvement comes at the cost of slightly slower settling time. These results highlight a trade-off between accuracy and transient response, motivating future research on multi-objective optimization to balance conflicting criteria such as robustness, energy efficiency, and response time.
Performance Enhancement of Photovoltaic Panels Using Passive Heatsink Cooling and Single-axis Solar Tracking Apribowo, Chico Hermanu Brillianto; Winda, Wiwik Nur; Maghfiroh, Hari; Iftadi, Irwan; Baballe, Muhammad Ahmad
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 2 (2025): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i2.13150

Abstract

Indonesia's persistent tropical climate and strong sunlight year-round lend themselves well to photovoltaic (PV) applications. However, prolonged sun exposure raises panel temperatures and reduces energy conversion efficiency. This study examines how to experimentally enhance the power output and efficiency of PV systems by combining single-axis solar tracking with passive heatsink cooling. On sunny days, two identical 50 W polycrystalline PV panels were evaluated in Surakarta, Indonesia. Four setups were tested: baseline (no tracking or cooling), tracking only, cooling only, and a combination of both. Temperature, voltage, and current data were gathered using calibrated INA219 and MLX90614 sensors. Results indicate the system can enhance efficiency and power output. Tracking alone improved power by 26.42% and efficiency by 2.16%; cooling using an aluminum heatsink boosted power by 40.28% and efficiency by 3.39%. Combining tracking and cooling yielded the highest power increase of 55.61%, with a 2.79% efficiency gain. These findings demonstrate the reduced efficiency benefits due to thermal effects despite higher irradiance in tracking systems. This research offers practical insights for optimizing PV performance in tropical regions and supports developing cost-effective, hybrid enhancement strategies.
Collision Avoidance in Mini Autonomous Electric Vehicles Using Artificial Potential Fields for Outdoor Environment Saputro, Joko Slamet; Juliatama, Hanif Wisti; Adriyanto, Feri; Maghfiroh, Hari; Apriaskar, Esa
International Journal of Robotics and Control Systems Vol 5, No 2 (2025)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v5i2.1708

Abstract

The rapid advancement of technology is driving the transition toward Society 5.0, where intelligent transportation systems enhance safety, efficiency, and sustainability. One of the biggest challenges in transportation is the high frequency of vehicle accidents, with approximately 80% attributed to driver error. To mitigate this, Advanced Driver Assistance Systems (ADAS) have been developed to improve vehicle autonomy and reduce accidents. This research proposes a potential field-based collision avoidance system for autonomous vehicle navigation, where the vehicle and obstacles act as positive poles, repelling each other, while the target destination serves as a negative pole, attracting the vehicle. Experimental results demonstrate a GPS positioning error of 1.55 m with a 66% success rate and LiDAR sensor accuracy of 96.4%, exceeding the required 95% threshold. Obstacle avoidance was tested with two safety thresholds (2 m and 2.5 m) across single- and two-obstacle scenarios. The 2 m threshold resulted in shorter travel distances (16.406 m vs. 16.535 m for 2.5 m) and faster completion times (19.036 s vs. 19.144 s), while the 2.5 m threshold provided greater clearance. GPS accuracy was significantly influenced by HDOP values and satellite count, with lower HDOP improving trajectory precision. The system successfully adjusted its trajectory in response to obstacles, ensuring effective real-time navigation.
Hybrid Catenary-Battery Trains for Non-Electrified Sections and Emergency Use Nizam, Muhammad; Maghfiroh, Hari; Putra, Mufti Reza Aulia; Jamaluddin, Anif; Inayati, Inayati
Automotive Experiences Vol 8 No 2 (2025)
Publisher : Automotive Laboratory of Universitas Muhammadiyah Magelang in collaboration with Association of Indonesian Vocational Educators (AIVE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/ae.13440

Abstract

The hybrid catenary–battery system offers a promising solution for railways operating in non-electrified sections and during emergencies, ensuring uninterrupted operation, enhanced safety, environmental sustainability, and cost efficiency. This study addresses the challenge of determining an appropriate battery size and introduces a novel rule-based Energy Management Strategy (EMS) with coasting mode to minimize energy consumption while meeting operational requirements. The novelty of this work lies in (i) a straightforward sizing method based on worst-case emergency scenarios and (ii) the integration of coasting-mode operation into a rule-based EMS for hybrid catenary–battery trains. Simulation results show that the proposed approach achieves up to 12.56% energy savings on 3% gradient tracks while fully supplying auxiliary loads, compared with baseline operation that provides only partial coverage. These results demonstrate a practical and scalable framework for designing efficient, reliable, and resilient railway transport systems.
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