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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

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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.

PROTOTIPE AUTOMATIC FEEDER DENGAN MONITORING IoT UNTUK PERIKANAN BIOFLOK LELE MASYARAKAT DUKUH PRAYUNAN Maghfiroh, Hari; Hermanu, Chico; Adriyanto, Feri
Jurnal Abdimas Vol 24, No 1 (2020): June
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LP2M), Universitas Negeri Semarang

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The Industrial Revolution 4.0 has brought many changes both positive and negative. The positive aspect is that there has been much use of automation and robots in the industrial world so that production can increase rapidly. While the negative angle, more and more human work is replaced by machines so that it reduces job opportunities. The existence of the industrial revolution 4.0 also brought a gap between the technology literacy group and the technology stutterer group (gaptek). Villagers are a large group from the second class. For this reason, a new business opportunity that can be carried out by the village community with secondary education level is urgently needed. Then the catfish bio-floc fisheries program was chosen. A touch of automation technology and the Internet of Things (IoT) is given to increase productivity and make people literate about the technological development of the industrial revolution era 4.0.

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

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.

PROTOTIPE AUTOMATIC FEEDER DENGAN MONITORING IoT UNTUK PERIKANAN BIOFLOK LELE MASYARAKAT DUKUH PRAYUNAN Maghfiroh, Hari; Hermanu, Chico; Adriyanto, Feri
Jurnal Abdimas Vol 24, No 1 (2020): June 2020
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/abdimas.v24i1.20636

The Industrial Revolution 4.0 has brought many changes both positive and negative. The positive aspect is that there has been much use of automation and robots in the industrial world so that production can increase rapidly. While the negative angle, more and more human work is replaced by machines so that it reduces job opportunities. The existence of the industrial revolution 4.0 also brought a gap between the technology literacy group and the technology stutterer group (gaptek). Villagers are a large group from the second class. For this reason, a new business opportunity that can be carried out by the village community with secondary education level is urgently needed. Then the catfish bio-floc fisheries program was chosen. A touch of automation technology and the Internet of Things (IoT) is given to increase productivity and make people literate about the technological development of the industrial revolution era 4.0.

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

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.

Low Pass Filter as Energy Management for Hybrid Energy Storage of Electric Vehicle: A Survey Maghfiroh, Hari; Wahyunggoro, Oyas; Cahyadi, Adha Imam
Automotive Experiences Vol 6 No 3 (2023)
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.9398

The transportation sector contributes up to 35% of carbon dioxide pollution. Electric Vehicles (EVs) offer a pollution-free alternative but face a crucial challenge in their battery-based Energy Storage System (ESS). The solution to the battery issues is combining it with other ESS with high power density called a Hybrid Energy Storage System (HESS). Energy Management Strategy (EMS) is used to distribute the power demand in the HESS. Low Pass Filters (LPFs) are one type of EMS that can be used to ensure the smooth flow of power between different energy storage elements. This article focuses on the pivotal role of Low Pass Filters (LPFs) within HESS for EVs, facilitating seamless power flow. The novelty lies in the comprehensive review of LPFs in this context, shedding light on their impact on energy management. Four LPF architecture classes are discussed: fixed cut-off, optimal cut-off, adaptive cut-off, and combination, referencing prior research. Additionally, a critical examination of challenges and limitations is provided, offering insights for researchers and practitioners.

Long Short-Term Memory vs Gated Recurrent Unit: A Literature Review on the Performance of Deep Learning Methods in Temperature Time Series Forecasting Furizal, Furizal; Fawait, Aldi Bastiatul; Maghfiroh, Hari; Maâ€™arif, Alfian; Firdaus, Asno Azzawagama; Suwarno, Iswanto
International Journal of Robotics and Control Systems Vol 4, No 3 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i3.1546

Temperature forecasting is a crucial aspect of meteorology and climate change studies, but challenges arise due to the complexity of time series data involving seasonal patterns and long-term trends. Traditional methods often fall short in handling this variability, necessitating more advanced solutions to enhance prediction accuracy. LSTM and GRU models have emerged as promising alternatives for modeling temperature data. This study is a literature review comparing the effectiveness of LSTM and GRU based on previous research in temperature forecasting. The goal of this review is to evaluate the performance of both models using various evaluation metrics such as MSE, RMSE, and MAE to identify gaps in previous research and suggest improvements for future studies. The method involves a comprehensive analysis of previous studies using LSTM and GRU for temperature forecasting. Assessment is based on RMSE values and other metrics to compare the accuracy and consistency of both models across different conditions and temperature datasets. The analysis results show that LSTM has an RMSE range of 0.37 to 2.28. While LSTM demonstrates good performance in handling long-term dependencies, GRU provides more stable and accurate performance with an RMSE range of 0.03 to 2.00. This review underscores the importance of selecting the appropriate model based on data characteristics to improve the reliability of temperature forecasting.

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

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.

Fuzzy logic method for making push notifications on monitoring system of IoT-based electric truck charging Al Madani Kurniawan, Aqsha; Khaula Amifia, Lora; Iskandar Riansyah, Moch.; Furizal, Furizal; Suwarno, Iswanto; Ma’arif, Alfian; Maghfiroh, Hari
Bulletin of Electrical Engineering and Informatics Vol 14, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i1.7412

To minimize the negligence when charging electric vehicles, it is deemed important to have an internet of things (IoT) based monitoring system using a notification feature. The monitoring system of electric vehicle battery charging used a voltage divider and temperature sensor (DS18B20) installed on the Arduino Mega 2560 microcontroller with the addition of an ESP8266 Wi-Fi module for sending microcontroller data into the Blynk platform. A notification feature was added as the reminder that the battery has been overcharging or overheating. This study applied the Mamdani fuzzy logic method to determine the conditions when notifications must appear. The results of the application of the Mamdani fuzzy logic method were able to determine the conditions for push notifications to appear using the parameters as desired; by so doing, it is possible to create a battery monitoring system with accurate push notification feature to prevent the battery from being overcharged and overheated.

Improving Dynamic Routing Protocol with Energy-aware Mechanism in Mobile Ad Hoc Network Mekonnen, Atinkut Molla; Munaye, Yirga Yayeh; Chekol, Yenework Belayneh; Bizuayehu, Getenesh Melie; Maghfiroh, Hari
Buletin Ilmiah Sarjana Teknik Elektro Vol. 6 No. 3 (2024): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v6i3.11994

A Mobile Ad hoc Network (MANET) is designed for specific communication needs, where nodes dynamically interact. In a MANET, mobile nodes self-configure and frequently adapt to changes in topology due to their ability to move freely. Each node operates as a router, forwarding data to other designated nodes within the network. Since these mobile nodes rely on battery power, energy management becomes critical. This paper addresses the challenges of routing in MANETs by improving the Dynamic Source Routing (DSR) protocol. The proposed enhancement, termed energy-aware DSR, aims to mitigate and reduce packet loss and improve the packet delivery ratio, which often suffers due to node energy depletion. Simulations conducted with the NS-3.26 tool across varying node counts demonstrate that the energy-aware DSR protocol significantly outperforms the traditional DSR in terms of efficiency and reliability.

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