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All Journal ELKHA : Jurnal Teknik Elektro Scientific Journal of Informatics PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Specta Journal of Technology Power Elektronik : Jurnal Orang Elektro SNTE
Dewanto, Muhammad Ridho
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Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mechanical Engineering Public Health Social Sciences

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Optimalisasi Filter Sumur Bor dan Embung ITK Berbasis Tenaga Surya untuk Peningkatan Pelayanan Sarana dan Prasarana Priyanto, Yun Tonce Kusuma; Farid, Mifta Nur; Dewanto, Muhammad Ridho; Sugiarto, Kharis; saputra, Riza Hadi
Power Elektronik : Jurnal Orang Elektro Vol 14, No 1 (2025): POWER ELEKTRONIK
Publisher : Politeknik Harapan Bersama Tegal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/polektro.v14i1.8494

Abstract

The limited supply of conventional energy poses a challenge in operating essential facilities at Institut Teknologi Kalimantan (ITK), particularly in the water filtration system and reservoir management. To address this issue, this study proposes the implementation of an off-grid Solar Power Plant as a solution to enhance energy independence and improve the quality of clean water services on campus. This research aims to design and analyze the performance of an off-grid Solar Power Plant system in supporting water pump operations while evaluating its efficiency in providing sustainable energy. The designed system utilizes three solar panels with a total capacity of 1,635 WP, which is sufficient to meet the 243 W AC pump power demand. The generated energy is regulated using a Maximum Power Point Tracker (MPPT) to optimize power conversion and minimize energy losses. Additionally, a 1,000 Watt Pure Sine Wave inverter is employed to ensure the pump operates stably, while excess energy is stored in a 24V 180 Ah battery to maintain system operation during cloudy conditions or nighttime. The calculations indicate an energy surplus of 5.33 kWh, reinforcing the system’s reliability in meeting the energy needs of the water pump. With a recorded pump efficiency of 55.5%, this study demonstrates that the designed PLTS system is effective in providing sustainable energy. The implementation of an off-grid Solar Power Plant has proven capable of supporting optimal water pump operations, enhancing campus energy independence, and reducing reliance on conventional electricity sources.
State of Charge Estimation on Lithium-Ion Batteries Using Particle Swarm Optimization Method Dewanto, Muhammad Ridho; Saputra, Riza Hadi; Sugiarto, Kharis; Saputra, Agung Adi
ELKHA : Jurnal Teknik Elektro Vol. 17 No.1 April 2025
Publisher : Faculty of Engineering, Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/elkha.v17i1.90020

Abstract

Lithium-ion battery management is crucial as their use grows in devices and electric vehicles. A key aspect is State of Charge (SoC) estimation, which indicates the battery's charge level at any given time. This research aims to develop a method that can provide accurate SoC estimates for Li-ion batteries using the Particle Swarm Optimization (PSO) method. In this research, a 12V 8.4 Ah Lithium-Ion battery was used as a test subject, utilizing a voltage sensor, ACS712 sensor, and LM35 temperature sensor to measure key parameters such as voltage, current, and temperature. The PSO approach was chosen because of its ability to find optimal solutions in complex search spaces, such as SoC estimation in batteries. Through a combination of the PSO algorithm and data generated from sensors, it is hoped that the SoC estimates produced can improve battery usage efficiency, extend service life, and increase the performance of systems that depend on batteries. PSO can provide more accurate predictions with smaller errors, both in terms of the RMSE value of 0.0391 and the MAPE value of 12.028%. The high accuracy of 87.972% of PSO also shows that this method is reliable for applications that require precise SoC predictions. It is hoped that the results of this research can become a basis for further research in the field of battery management and metaheuristic algorithm optimization. After all, this research aims to enhance battery management systems and deepen understanding of PSO-based SoC estimation.
State Of Charge Estimation on Lithium ION Batteries Using Quantum Neural Network Situmorang, Raftonado; Dewanto, Muhammad Ridho; Hasanah, Barokatun; Deliasgarin, Kholiq; Oktafian, Bagus Gilang
SPECTA Journal of Technology Vol. 9 No. 2 (2025): Specta Journal of Technology
Publisher : LPPM ITK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35718/specta.v9i2.1305

Abstract

Battery applications can be found in electric vehicles, renewable energy power plants and various other portable devices. In this final project research, the author uses the Quantum Neural Network (QNN) method to estimate the State of Charge (SoC) on a lithium-ion battery designed using PYTHON. This research includes the design of a prototype SoC estimation system on lithium-ion batteries using the QNN method, real-time SoC data collection, and comparison of SoC estimation performance using QNN with real-time data. The results of real-time testing of lithium-ion batteries using ACS712 voltage and current sensors for five cycles show the following voltage results: first cycle 10.70 V to 12.68 V, second cycle 10.56 V to 12.66 V, third cycle 10.60 V to 12.69 V, fourth cycle 10.60 V to 12.00 V, and the fifth cycle 10.41 V to 12.07 V. Meanwhile, the current sensor results for five cycles showed a range of 0.1 A to 0.5 A. Each test result per cycle showed a higher increase, although there were small fluctuations, and the overall trend line showed the consistency of the voltage sensor's performance without significant degradation during repeated tests, indicating good stability of the voltage sensor. Then, methods with qubit rotation, linear entanglement, and Neural Network were tested. SoC prediction results using QNN with qubit rotation showed MAPE and RMSE values of 0.14 and 61%, respectively. Furthermore, testing the SoC prediction results on QNN with linear entanglement shows MAPE and RMSE values of 0.08 and 29%, respectively. While the SoC prediction results.
IoT-Based Application Design for Battery Discharge Condition With C-Rate Variation Saputra, Riza Hadi; Giyantara, Andhika; Dewanto, Muhammad Ridho; Sawung, Jheskia Ardito
ELKHA : Jurnal Teknik Elektro Vol. 17 No.2 October 2025
Publisher : Faculty of Engineering, Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/elkha.v17i2.96225

Abstract

Lithium-ion (Li-ion) batteries are one of the most widely used energy storage technologies due to their advantages in high energy density, fast rechargeability, and efficiency. However, behind these advantages lie the weaknesses of lithium-ion batteries, namely that their performance and lifespan are greatly influenced by factors such as C-rate and lithium-ion battery temperature. A high C-rate can increase temperature and accelerate battery degradation, while a low C-rate tends to result in lower temperatures and more optimal capacity. This study aims to design an Internet of Things (IoT)-based State of Charge (SoC) monitoring system capable of real-time battery condition monitoring. The system uses an ESP32 microcontroller connected to a voltage sensor, an ACS712 current sensor, and an LM35 temperature sensor. The collected data is sent to Firebase and displayed through an Android application based on MIT App Inventor. The study focused on discharge cycles with varying C-rates: 1C, C/2, C/5, C/10, and C/20. SoC estimation was performed using the coulomb counting method. The results showed that as the C-rate decreases, the obtained capacity tends to increase, even exceeding the nominal capacity at C/20. Accuracy evaluation using RMSE yielded error values ranging from 0.12% to 4.04%. This system can serve as an effective solution for IoT-based battery monitoring
Pemberdayaan Masyarakat LKSA Aisyiyah Balikpapan melalui Pengembangbiakkan Ikan Lele dengan Pakan Otomatis: Community Empowerment of Aisyiyah Balikpapan LKSA through Catfish Breeding with Automatic Feeding Saputra, Riza Hadi; Dewanto, Muhammad Ridho; Rosalina, Rosalina
PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Vol. 9 No. 1 (2024): PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat
Publisher : Institute for Research and Community Services Universitas Muhammadiyah Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33084/pengabdianmu.v9i1.5858

Abstract

Catfish breeding using an automatic feeding system involves four crucial stages to achieve success in this endeavor. The first stage in this process is the survey stage, which involves a field survey by visiting the Aisyiyah Children's Social Welfare Institution (LKSA). The second stage is the tool preparation stage. This process begins with purchasing the necessary equipment based on the results of the survey that has been conducted. The third stage is the tool installation stage. This stage begins with the land preparation, including leveling the land where the catfish ponds will be installed. As a further step, bricks are used around the perimeter of the catfish pond to support the pond foundation and prevent collapse. Then, an automatic feed device was installed to support the automatic feeding system according to a predetermined schedule. The last stage is the equipment handover stage. This stage marks the completion of the installation and preparation process and signifies the start of the active phase in catfish farming using the automatic feed system. Success in the implementation of each of these stages has direct implications for the success and sustainability of the catfish farming business at LKSA Aisyiyah.
Estimation of Lithium-Ion Battery Health in Electric Bicycles Using Internal Resistance Measurement Method Saputra, Riza Hadi; Dewanto, Muhammad Ridho; Maulana, Hadi
ELKHA : Jurnal Teknik Elektro Vol. 16 No.1 April 2024
Publisher : Faculty of Engineering, Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/elkha.v16i1.78316

Abstract

This study evaluates the performance of a 36 Volt 10 Ah battery in an electric bicycle with a 350-Watt Brushless DC (BLDC) motor as an environmentally friendly alternative to overcome the negative impacts of motorized vehicle use in Indonesia. In addition, this study measured the State of Health battery"™s value of internal resistance, which is different from other studies that use capacity fading. With a focus on maximum travel distance and travel time, experiments were conducted without load and with a 70kg load. The no-load test was conducted only once, resulting in a travel time of 600 minutes and a distance of 330.1 Km. Although the battery was not discharged, the results were not in line with expectations, so the no-load test was only conducted once. In the 70kg load test, six trials were conducted with variable measurements of distance, battery voltage, and battery resistance. Results showed variations in distance between 50.7 km and 53.1 km, and travel time between 151 and 160 minutes. The battery voltage varied from 31.316 Volts to 31.850 Volts. The resistance in the battery also showed an increase of about 0.0001 ohms from 0.1132 ohms to 0.1139 ohms. Overall, the results from the study showed that as time and usage progressed, the battery voltage and internal resistance values tended to increase, while the distance and travel time tended to decrease. The internal resistance measurement method proved to be effective in assessing battery health as the State of Health value decreased throughout the experiment.
YOLO vs. CNN Algorithms: A Comparative Study in Masked Face Recognition Dewanto, Muhammad Ridho; Farid, Mifta Nur; Rafdi Syah, Muhammad Abby; Firdaus, Aji Akbar; Arof, Hamzah
Scientific Journal of Informatics Vol 11, No 1 (2024): February 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i1.48723

Abstract

Purpose: This research investigates the effectiveness of YOLO (You Only Look Once) and Convolutional Neural Network (CNN) in real-time face mask recognition, addressing the challenges posed by mask-wearing in infectious disease prevention.Method: Utilizing a diverse dataset and employing YOLO's object detection and a combined Haar Cascade Algorithm with CNN, the study evaluated key performance indicators, including accuracy, framerate, and F1 Score.Results: Results indicated that CNN outperformed YOLO in accuracy (99.3% vs. 79.3%) but operated at a slightly lower framerate. YOLO excelled in recall and precision, presenting a compelling choice for specific application needs. The research underscores the importance of considering factors beyond accuracy for informed decision-making in the realm of face mask recognition.Novelty: This research evaluates the real-time performance of YOLO and CNN algorithms in masked face recognition, highlighting the crucial balance between framerate efficiency and detection accuracy.
Modification of Sigma-Delta DAC for Digital Spike Signal Processing Dewanto, Muhammad Ridho; Hizbullah, Mohammad Naufal; Sugiarto, Kharis
Seminar Nasional Teknik Elektro Vol. 4 No. 1 (2025): SNTE III
Publisher : Forum Pendidikan Tinggi Teknik Elektro Indonesia Pusat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46962/snte.25.096

Abstract

his study aims to modify the architecture of a Sigma-Delta Digital-to-Analog Converter (DAC) based on FPGA to support the conversion of digital spike signals to analog in neuromorphic systems. The main focus of the modification lies in increasing the order of the noise loop filter and implementing a Multi-Stage Noise Shaping (MASH) structure consisting of a combination of 1-bit and 3-bit DACs. The modification process was carried out in the truncation and feedback stages and simulated using the Verilog programming language on the Altera Cyclone V FPGA. Evaluation was conducted using tonic spike inputs representing a 15 Hz sinusoidal signal. The results show improvements in the linearity of the analog output signal, enhancement of quality parameters such as SNR and ENOB, and reduced latency. Nevertheless, some challenges remain related to truncation errors that have not been fully addressed.
Co-Authors Arof, Hamzah Barokatun Hasanah, Barokatun Deliasgarin, Kholiq Farid, Mifta Nur Firdaus, Aji Akbar Giyantara, Andhika Hizbullah, Mohammad Naufal Maulana, Hadi Oktafian, Bagus Gilang Priyanto, Yun Tonce Kusuma Rafdi Syah, Muhammad Abby Rosalina Rosalina Saputra, Agung Adi Saputra, Riza Hadi Sawung, Jheskia Ardito Situmorang, Raftonado Sugiarto, Kharis