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Diky Zakaria
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INDONESIA
Journal of Mechatronics and Artificial Intelligence
Published by Universitas Pendidikan Indonesia
ISSN : 3062729X     EISSN : 30484227     DOI : https://doi.org/10.17509/jmai.v1i1
Core Subject :
The Journal of Mechatronics and Artificial Intelligence (JMAI) (E-ISSN 3048-4227 P-ISSN 3062-729X) serves as a platform for disseminating scholarly research related to the fields of mechatronics and artificial intelligence, as well as related sub-disciplines. We extend an invitation to researchers, engineers, senior researchers, lecturers, and students from Indonesia as well as countries across the globe to disseminate their research findings through our journal platform. A comprehensive and thorough review process will be implemented to guarantee the production of high-quality articles. The types of research that can be published on JMAI are Literature review articles, Empirical studies, Case studies, Theoretical articles. The scope of the journal are Mechatronics, Industrial automation, Robotics, Control and Systems, Sensors, Electronics, Electrical Machines, Image processing and pattern recognition, Artificial Intelligence, Machine learning, Instrumentation and Measurement, Agents and multi-agent systems, Natural language and Energy.
Arjuna Subject : -
Articles 26 Documents
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Design and Simulation of a Hybrid Solar and Wind Power Plant System in South Garut Using HOMER Software Aditya Aditya; Ifkar Usrah; Linda Faridah
Journal of Mechatronics and Artificial Intelligence Vol. 2 No. 1 (2025): JMAI: June 2025
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jmai.v2i1.82865

Abstract

The increasing demand for sustainable energy highlights the urgency of integrating renewable energy sources into power generation systems. South Garut, Indonesia, offers significant potential for solar and wind energy, particularly in the coastal area of Cibalong District. This study aims to design and simulate a hybrid solar and wind power plant system optimized using the HOMER software. Field observations, energy consumption data collection, and analysis of local renewable energy resources were conducted to establish the system parameters. The HOMER software was utilized to perform simulation, optimization, and sensitivity analysis, considering factors such as Net Present Cost (NPC), Cost of Energy (COE), Return on Investment (ROI), and Internal Rate of Return (IRR). The simulation results indicate that integrating photovoltaic panels and wind turbines within an on-grid hybrid configuration significantly enhances system reliability and cost-efficiency. The optimal system configuration achieves a competitive COE while ensuring long-term energy sustainability. This research provides a reference model for the development of renewable energy-based power systems in remote coastal areas, supporting national initiatives to increase the share of renewable energy in Indonesia’s energy mix.
Design and Fabrication of an Automatic Pet Food Dispenser Faida Bako Amans; Umar Ali Umar
Journal of Mechatronics and Artificial Intelligence Vol. 2 No. 1 (2025): JMAI: June 2025
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jmai.v2i1.80389

Abstract

This study presents the design and fabrication of an automatic pet food dispenser system, aimed at providing controlled, precise, and timely feeding for pets. The system utilizes a 12V DC motor, a load cell for weight measurement, a 4x4 keypad for user input, an LCD for real-time feedback, and a real-time clock (RTC) for scheduling. The screw feeder mechanism driven by the DC motor ensures controlled dispensing, halting automatically when the load cell confirms the desired weight. An emergency function allows feeding outside regular intervals. Tests with two pet food types (small and large kibbles) showed a ±10% margin of error, demonstrating reliable functionality. This solution offers practical, energy- efficient automation for pet care, with potential for enhancements such as IoT integration and advanced power management.
Social Media Dynamics: Twitter Users’ Responses to the Presence of Naturalized Players in Indonesia's National Football Team Sony Harianto; Windu Gata
Journal of Mechatronics and Artificial Intelligence Vol. 2 No. 1 (2025): JMAI: June 2025
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jmai.v2i1.80033

Abstract

Public discourse on the naturalization of players in Indonesia’s national football team continues to grow, with social media platforms such as Twitter becoming primary outlets for expressing opinions. This study employs advanced sentiment analysis techniques, utilizing IndoBERT—a deep learning model specifically designed for the Indonesian language—to analyze the sentiments of Twitter users. The analytical process includes data preprocessing, sentiment distribution visualization, and model performance evaluation. Findings reveal that IndoBERT captures public sentiments more comprehensively and accurately than conventional sentiment analysis models. Sentiment polarity is significantly influenced by factors such as player performance, public expectations, and media narratives. This study offers practical insights for policymakers in Indonesian football to support data-driven strategic decision-making. Furthermore, it underscores the value of natural language processing (NLP) and sentiment analysis in understanding complex socio-cultural dynamics in the digital era.
The Effect of AI-Generated Content on Brand Identity Consistency in Social Media: A Systematic Literature Review Indra Komara; Agus Juhana
Journal of Mechatronics and Artificial Intelligence Vol. 2 No. 1 (2025): JMAI: June 2025
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jmai.v2i1.78626

Abstract

The consistency of brand identity on social media platforms is pivotal for fostering customer recognition, trust, and engagement. This research endeavor aims to investigate the impact of AI-generated content on the consistency of brand identity through the application of a systematic literature review methodology. The research methodology adheres to the PRISMA 2020 guidelines in order to identify, screen, and analyze pertinent scholarly articles. This inquiry poses three primary questions: in what manner does the utilization of AI in the creation of visual content influence the consistency of brand identity on social media; how does the consistency of brand identity produced by AI-generated content compare to that of content created through traditional methods; and what strategies can be implemented to ensure visual aesthetic coherence when employing AI-generated content in branding efforts? The findings indicate that although AI possesses the capacity to enhance efficiency and produce high-quality content, challenges pertaining to authenticity and consumer perception persist. Consequently, it is imperative for brands to adopt an ethical and transparent methodology concerning the deployment of AI technologies. This study advocates for companies to take a more proactive stance in incorporating human oversight and relevant instruments to guarantee that AI-generated content remains consistent, authentic, and aligned with the fundamental values of the brand.
Analysis of Energy-Saving Opportunities at SMKN 3 Kuningan Sofia Nurul Fajri; Nundang Busaeri; Imam Taufiqurrahman
Journal of Mechatronics and Artificial Intelligence Vol. 2 No. 1 (2025): JMAI: June 2025
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jmai.v2i1.82904

Abstract

This research presents the results of an energy audit at SMKN 3 Kuningan, which aims to identify energy saving opportunities in the school's electrical system. The audit focused on two main energy consumption systems, lighting and air conditioning (AC). The analysis was conducted based on electricity consumption data and Energy Consumption Intensity (IKE) standards. The results show that the lighting system still uses conventional TL and incandescent lamps, which waste energy. Replacing with energy-saving LED lamps can save around 571 kWh per month. In addition, the AC units used mainly have low efficiency. Replacing with energy-saving AC and adjusting operating hours results in additional savings of 5,718.29 kWh per month. Overall, the school has the potential to reduce electricity consumption by 6,289.29 kWh per month. The implementation of this recommendation is also able to reduce the IKE value from 105,321 kWh/m²/year to 103,924 kWh/m²/year, closer to the national efficiency standard according to SNI 03-6197-2000 and the regulations of the Ministry of Energy and Mineral Resources. This research emphasizes the importance of regular energy audits in educational institutions as a strategic step in operational cost efficiency and contribution to environmental sustainability.
Mamdani Fuzzy Logic-Based Room Temperature Monitoring and Control System Trisiani Dewi Hendrawati; Fikri Arif Wicaksana; Panji Narputro; Samirah Rahayu
Journal of Mechatronics and Artificial Intelligence Vol. 2 No. 1 (2025): JMAI: June 2025
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jmai.v2i2.88461

Abstract

Automatic room temperature control is a crucial need for maintaining comfort and energy efficiency, especially in enclosed environments such as offices, laboratories, and homes. This research aims to design and develop a room temperature monitoring and control system based on Mamdani fuzzy logic. The system utilizes a temperature sensor to monitor real-time environmental conditions and actuators (fans or heaters) as outputs to adjust the temperature. The Mamdani fuzzy logic method is chosen for its ability to handle uncertainty and provide decisions that resemble human reasoning. Test results show that the system can maintain the room temperature within the desired range responsively and efficiently. By implementing this system, thermal comfort can be achieved automatically without manual intervention, while also supporting energy savings in the operation of cooling and heating devices.
Design and Implementation of a Digital PID Controller for DC–DC Buck Converter with MATLAB Hadfina Azra Syahidah; Ariya Jembar Pangestu; Muhammad Salman Al Farisi; Radinald Ferdiansyah; Refaldi Nazhr Warnata; Mochamad Zulfikar; Muhammad Adli Rizqulloh
Journal of Mechatronics and Artificial Intelligence Vol. 2 No. 2 (2025): JMAI: December 2025
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jmai.v2i2.79904

Abstract

This study focuses on the design and implementation of a digital Proportional-Integral-Derivative (PID) controller for a DC-DC buck converter using MATLAB. The main issue addressed is the need for better voltage regulation in power electronics applications, which is critical to maintaining system stability and performance. The objective of this study is to develop a robust control strategy that minimizes output overvoltage and improves accuracy under varying load conditions. The methodology used involves the development of a discrete-time PID controller, which is simulated in MATLAB to analyze its performance. The results in MATLAB show that the digital PID controller successfully limits overvoltage and maintains output voltage stability, even with significant load variations. Further experimental validation confirms the simulation results, demonstrating the controller’s ability to adapt to real-world conditions. The successful implementation and validation of the controller using MATLAB underscores its potential to improve the efficiency and reliability of power conversion systems.
Study of the Effect of the Use of Series Reactive Power Compensators on the Increase in Inductive Load Power Factor with Magnetic Energy Recovery Switches in Household Environments Adi Nugraha; Tartila Dinar Haqiqi; Lazuardi Akmal Islami; Panji Narputro
Journal of Mechatronics and Artificial Intelligence Vol. 2 No. 2 (2025): JMAI: December 2025
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jmai.v2i2.83220

Abstract

The use of inductive loads in modern household electrical installations is increasing, particularly in multi-story homes equipped with elevators, water pump drive motors, and generators. Such inductive loads lead to a decrease in power factor due to the dominance of reactive power, which negatively affects the efficiency and cost of electricity consumption. This study aims to improve the power factor in a three-story residential electrical system by implementing a reactive compensation method using a Magnetic Energy Recovery Switch (MERS) circuit. The system design and analysis are based on active power data obtained through the Autodesk Revit 2024 application, with load parameters sourced from the F-H05 elevator, Grundfos pump motor, and Weichai Power generator. Simulation was carried out using PSIM software to determine the optimal capacitor value and triggering angle for the IRF820 MOSFET. The simulation results show that the application of MERS significantly improves the power factor, making the system more efficient and cost-effective.
Performance Analysis of Dijkstra and A-star Algorithm in Maritime Navigation Pathfinding Ali Chandra Rizki; Keyzar Rasya Athallah; Syauqiy Mutiara Siddiq; Zahra Kusmanidar; Diky Zakaria
Journal of Mechatronics and Artificial Intelligence Vol. 2 No. 2 (2025): JMAI: December 2025
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jmai.v2i2.84983

Abstract

This study explores various algorithms and methodologies for path planning and decision-making in diverse environments, including maritime distribution and logistics. The research highlights the importance of COLREG rules in designing collision avoidance algorithms for Maritime Autonomous Surface Ships (MASS), emphasizing the need for algorithms that adapt to specific maritime parameters. A Multiple-Criteria Decision-Making (MCDM) approach combined with Dijkstra’s algorithm is presented to optimize route distribution in logistics, taking into account parameters such as cost, distance, congestion, and risk. Experimental path planning methods using A-star and Dijkstra algorithms are discussed for navigating slag disposal sites that emit natural radiation, demonstrating the adaptability of these algorithms in hazardous environments. The study also investigates dynamic path planning algorithms, such as DAA-Star, which incorporate time and risk cost factors to enhance the safety and efficiency of navigation. Integrating various algorithms and considering specific environmental parameters can significantly improve path planning and decision-making processes in maritime and logistics contexts.
A Comparative Study of Data-Driven Control Tuning: VRFT and FRIT for DC Motor Speed Regulation Dede Irawan Saputra; Dadang Lukman Hakim
Journal of Mechatronics and Artificial Intelligence Vol. 2 No. 2 (2025): JMAI: December 2025
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jmai.v2i2.88236

Abstract

This study compares two data-driven control tuning methods Virtual Reference Feedback Tuning (VRFT), and Fictitious Reference Iterative Tuning (FRIT) applied to a DC motor speed control system. Both methods aim to achieve a predefined closed-loop behaviour without explicit plant modelling, relying instead on measured input–output data. For the VRFT method, single-shot open-loop data were collected using a PRBS signal to excite the DC motor, while FRIT used a single-shot closed-loop experiment under an initial PI controller. Each method used the same reference model, a first-order system with a 2 second time constant, to guide the tuning process. The VRFT approach produced a 6-DOF controller through least-squares optimization, whereas the FRIT method refined the parameters of a PI controller by minimizing a defined cost function. Simulations conducted at target speeds of 60 and 100 RPM demonstrated that both controllers delivered comparable tracking performance, despite having different structural designs. These findings confirm that both VRFT and FRIT can generate effective control strategies from limited data, providing design flexibility while still achieving the desired closed-loop behaviour.

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