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International Journal of Electrical, Computer, and Biomedical Engineering (IJECBE)
Published by Universitas Indonesia
ISSN : -     EISSN : 30265258     DOI : https://doi.org/10.62146/ijecbe.v2i1
Core Subject : Health, Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering Materials Science & Nanotechnology Medicine & Pharmacology
The International Journal of Electrical, Computer, and Biomedical Engineering (IJECBE) is an international journal that is the bridge for publishing research results in electrical, computer, and biomedical engineering. The journal is published bi-annually by the Electrical Engineering Department, Faculty of Engineering, Universitas Indonesia. All papers will be blind-reviewed. Accepted papers will be available online (free access) The journal publishes original papers which cover but is not limited to Electronics and Nanoelectronicsc Nanoelectronics and nanophotonic devices; Nano and microelectromechanical systems (NEMS/MEMS); Nanomaterials; Quantum information and computation; Electronics circuits, systems on chips, RF electronics, and RFID; Imaging and sensing technologies; Innovative teaching and learning mechanism in nanotechnology education; Nanotechnologies for medical applications. Electrical Engineering Antennas, microwave, terahertz wave, photonics systems, and free-space optical communications; Broadband communications: RF wireless and fiber optics; Telecommunication Engineering; Power and energy, power electronics, renewable energy source, and system; Intelligent Robotics, autonomous vehicles systems, and advanced control systems; Computational Engineering. Computer Engineering Architecture, Compiler Optimization, and Embedded Systems; Networks, Distributed Systems, and Security; High-performance Computing; Human-Computer Interaction (HCI); Robotics and Artificial Intelligence; Software Engineering and Programming Language; Signal and Image Processing. Biomedical Engineering Cell and Tissue Engineering; Biomaterial; Biomedical Instrumentation; Medical Imaging.
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 83 Documents
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Design and Development of a Therapeutic Device for Drop Hand Patienst Setyawan, Rahmatul Yoga; Purnamaningsih, Retno Wigajatri
International Journal of Electrical, Computer, and Biomedical Engineering Vol. 2 No. 3 (2024)
Publisher : Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62146/ijecbe.v2i3.53

Abstract

Drop hand is a condition where a person's wrist or fingers experience difficulty and weakness in performing extension and flexion movements. This paper reports the design and development of a therapeutic device for individuals with drop hand, capable of performing passive training movements, electrical stimulation, and monitoring muscle strength. The device consists of a servo motor (MG995) for passive training movements, an IC NE555 specifically used for stimulation, and a Myoware muscle sensor to monitor muscle strength in the hands of individuals with drop hand. The device is also equipped with a NodeMCU ESP8266 microcontroller that can connect to a WiFi network, allowing muscle sensor readings to be stored in Google Sheets. Initial tests showed that the device could lift weights up to 1 kg, generate electrical stimulation frequencies ranging from 2.75 Hz to 18.2 Hz, and that muscle strength monitoring could be performed in real time.
An Implementation of Quasi-Newton Algorithm for Fast-charging Lithium-Ion Battery (LIB) Optimization in Electric Vehicle Application Anjarani, Mahmudda Mitra Anjarani; Raharya, Naufan
International Journal of Electrical, Computer, and Biomedical Engineering Vol. 2 No. 2 (2024)
Publisher : Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62146/ijecbe.v2i2.54

Abstract

Lithium-Ion Battery (LIB) is still an effective alternative technology in maximizing the efficiency of electric vehicles (EV). The application of EVs has had a significant impact in order to reduce the issue of global problems - reducing carbon gas emissions. The LIB charging mechanism with the fast-charging method is an alternative to the application of EVs on a more massive scale. However, the dynamics of the battery where the battery work function can decrease over time will affect battery performance. In addition, fast-charging efforts at LIB with maximum speed have the impact of increasing the risk of battery temperature and the existence of a larger gap in battery degradation. This paper proposes the application of Limited-Memory-Broyden-Fletcher-Goldfarb-ShannoBound Constrained (L-BFGS-B) algorithm for Lithium-Ion Battery (LIB) fast-charging optimization as an innovative solution approach in dealing with the complex LIB fastcharging dynamics. The results show that this approach is able to improve fast-charging speed and efficiency.
Implementation of Diffusion Variational Autoencoder for Stock Price Prediction with the Integration of Historical and Market Sentiment Data Ardisurya; Rizkinia, Mia
International Journal of Electrical, Computer, and Biomedical Engineering Vol. 2 No. 2 (2024)
Publisher : Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62146/ijecbe.v2i2.55

Abstract

This study aims to predict stock prices using a Diffusion Variational Autoencoder (D-VAE) model that integrates technical data and market sentiment. Technical data is obtained from historical stock prices and trading volume, while sentiment data is derived from financial news analyzed using the IndoBERT model for sentiment classification. The research findings indicate that the integration of sentiment data in the D-VAE model enhances the accuracy of stock price predictions compared to a model that uses only technical data. Model evaluation is conducted using metrics such as Mean Squared Error (MSE), Mean Absolute Error (MAE), and R-squared (R²). The model with sentiment data integration has an MSE of 2753.204, MAE of 42.751, and R² of 0.94489, which are better than the model without sentiment data integration. This study demonstrates that the use of sentiment analysis can significantly contribute to improving stock price prediction performance using machine learning technology.
Anomaly Detection in Imbalance Secure Water Treatment Dataset Using LSTM-DC-Wasserstein Generative Adversarial Network with Gradient Penalty Kevin, Jonathan Marshell; Raharya, Naufan
International Journal of Electrical, Computer, and Biomedical Engineering Vol. 2 No. 3 (2024)
Publisher : Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62146/ijecbe.v2i3.56

Abstract

In modern industrial systems, particularly with the advancement of the Internet of Things (IoT), industry players can record machine and system data for comprehensive analysis. This capability is crucial for detecting anomalies and taking necessary corrective actions.However, it is common for manufacturers to lack recorded anomaly datasets, especially for newly operational systems. In this paper, we develop a model to detect anomalies in an imbalanced dataset from the Secure Water Treatment (SWaT) system. The performance of the proposed model is compared with previous works, demonstrating significant improvements in anomaly detection capabilities where it achieves accuracy of 0.9546, precision of 0.9086, recall of 0.6654, and F1 score of 0.7681
Implementation of U-Net for Paddy Field Mapping Using Very High-Resolution Satellite Imagery Isbat, Faiz Khairul; Rizkinia, Mia; Sudiana, Dodi
International Journal of Electrical, Computer, and Biomedical Engineering Vol. 2 No. 3 (2024)
Publisher : Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62146/ijecbe.v2i3.57

Abstract

Mapping rice fields using remote sensing is one method that can be used to determine the number of rice fields, especially in Indonesia. Using this method can increase effectiveness in agricultural resource management. This research uses Pleiades optical satellite image data with very high resolution which is capable of displaying data information on a larger scale. The rice field classification model in this study uses U-net to classifier between rice fields and non-rice fields. The performance of applying this model for the classification of paddy fields and non-rice fields is 96%. These results show that the U-net model is capable of classifying small rice fields with high accuracy
A Design of Economically Feasible Hybrid Energy System with Renewable Energy Ratio Priority Sibarani, Michael Bonardo Siswono; Jufri, Fauzan Hanif; Samual, Muhammad Gillfran; Widayat, Aditya Anindito; Sudiarto, Budi
International Journal of Electrical, Computer, and Biomedical Engineering Vol. 2 No. 2 (2024)
Publisher : Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62146/ijecbe.v2i2.60

Abstract

The reduction of fossil fuels which produce CO2 emission that damage the environment, can be done by implementing renewable energy-based power generations, such as solar and wind. This research designs a hybrid energy system by optimizing the use of existing diesel generators through the integration of renewable energy sources, such as solar photovoltaic and micro wind turbine, and is equipped with an energy storage system. This research uses HOMER Pro software to determine the optimal capacity of hybrid system components, and to calculate the cost of energy (CoE). Furthermore, the hybrid system configuration is analyzed by applying several objectives. The objectives of the hybrid system design are to prioritize a maximum renewable energy penetration ratio within permitted annual capacity shortage and with the CoE lower than the existing CoE. The research results show that the proposed hybrid energy system can provide a renewable energy penetration ratio of 57.1% with CoE of IDR 3,510/kWh.
Blackout Recovery Scenario in a Combined-Cycle Power Plant via Line Charging and Internal Cross-Supply: A Techno-Economic Comparative Analysis Warih, Gamal Fiqih Handono; Jufri, Fauzan Hanif; Samual, Muhammad Gillfran; Hudaya, Chairul
International Journal of Electrical, Computer, and Biomedical Engineering Vol. 2 No. 2 (2024)
Publisher : Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62146/ijecbe.v2i2.61

Abstract

The readiness of fast response power plants, such as Combined-Cycle Power Plant (CCCP), following a blackout in the power system shall be maintained to preserve the availability of the supply. Hence, blackout recovery scenario is usually prepared and considered as one of the measures to achieve the system readiness after blackout. This study presents a techno-economic comparative analysis between two blackout recovery methods, namely via line charging and internal cross-supply, in CCCP Priok, Indonesia. It analyzes the historical data of the relationship of the active power contribution to the frequency, and then obtains the appropriate settings for the power plant parameters. From the technical perspective, the gain value or participation factor of this plant is 49 MW/Hz with 6% droop setting and 0.029 Hz of deadband frequency. It is found that a load set point lower than 2.49 MW can lead to grid synchronization failure since there are self-consumption loads on each gas turbine. Moreover, to prevent the risk of reverse power and to achieve a successful internal cross-supply scenario, the minimum load setting shall be adjusted to 3 MW. Meanwhile, from an economic perspective, the results show that a successful internal cross-supply method may save up to IDR 2.7 billion compared with line charging method.
Comparison Performance Analysis of PI and PI-ANFIS in VSC-HVDC Transmission Systems Aziz, Muhamad Abdul; Husnayain, Faiz
International Journal of Electrical, Computer, and Biomedical Engineering Vol. 2 No. 3 (2024)
Publisher : Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62146/ijecbe.v2i3.66

Abstract

Voltage Source Converter-High Voltage Direct Current (VSC-HVDC) transmission systems are preferred for long-distance power transmission due to their flexibility and stability. However, maintaining optimal performance and stability during transient conditions and disturbances is challenging. This research analyzes the performance of VSC-HVDC systems using Proportional-Integral Adaptive Neuro-Fuzzy Inference System (PI-ANFIS) control compared to conventional PI control. A VSC-HVDC system model with PI control provides the basis for generating input-output data to train the ANFIS model. Subsequently, a VSC-HVDC model with PI-ANFIS control is developed and optimized. Performance evaluation under transient conditions and both permanent and temporary disturbances reveals that PI-ANFIS significantly enhances system performance. PI-ANFIS reduces overshoot, accelerates settling time in active power, reactive power, and DC voltage control, and improves stability and recovery time during disturbances. The adaptability and learning capabilities of ANFIS offer additional flexibility for dynamic conditions and unexpected disturbances. This study highlights intelligent control technology advancements, promoting reliable and adaptable power transmission systems, and lays the groundwork for future research and practical applications of PI-ANFIS control in VSC-HVDC systems.
Analysis of Bare Uniform Fiber Bragg Grating Sensor for Measuring Strain on the Landing Gear of the LSU-02 Unmanned Aircraft Anwar, Rudi Choirul; Purnamaningsih, Retno Wigajatri; Rahardjo, Sasono; Hamidah, Maratul; Martha, Aryandi; Firdaus, Muhammad Yusha; Pramudya, Tinova
International Journal of Electrical, Computer, and Biomedical Engineering Vol. 2 No. 3 (2024)
Publisher : Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62146/ijecbe.v2i3.70

Abstract

This paper reports the results of testing a bare uniform FBG sensor for measuring strain occurring on the landing gear of an unmanned aircraft. The landing gear used in this research is made from carbon fiber, known for its high strength and stiffness. The FBG sensor is positioned 20 cm from the center point of the landing gear, specifically at the curved section, to optimize strain detection. Static testing to measure strain was conducted by applying varying mass loads from 0 to 9 kilograms to test the sensor's response to load changes. Measurement results show a constant measurement threshold at a load of 50 grams, indicating sensor stability within that load range, with a measurement resolution of 0.1654 microstrain. Comparison of FBG measurement results with the BLFAB-55 strain gauge sensor revealed a measurement difference of 5.9%. Further research was conducted by introducing disturbances in the form of wind at speeds of 5 m/s and 10 m/s, and temperature disturbances of 30°C and 45°C. The results showed that the 45°C temperature disturbance had the most significant impact on the strain changes measured by the FBG, with an increase in strain value of 265% compared to when there was no disturbance.
Optimal Battery Energy Storage System Placement Strategy in Central Java Electrical System for Voltage and Losses Improvement Fikry, Hafizh Al; Samual, Muhammad Gillfran; Sudiarto, Budi
International Journal of Electrical, Computer, and Biomedical Engineering Vol. 2 No. 3 (2024)
Publisher : Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62146/ijecbe.v2i3.75

Abstract

Over the past few decades, advances in energy storage technology, particularly in the form of Battery Energy Storage Systems (BESS), have provided innovative solutions to address various challenges in the power grid such as voltage fluctuations and high levels of losses, which negatively impact the efficiency and quality of electricity provision. BESS has advantages over other energy storage technologies such as having lower costs, faster response times to power equipment or devices, and increased efficiency and flexibility. The purpose of this research is to determine the optimal capacity and location of the placement of BESS to get an improvement in the voltage profile and losses in the Central Java Province power system. In this study, BESS is incorporated into the Jelok substation based on the calculation method under day and night conditions, which will be sought for the most optimal placement. After getting the most optimal placement, the optimal BESS capacity based on the calculation method, 15 MWh, and 25 MWh will be compared. The effect of optimum BESS placement and sizing of up to 0.0035 pu, and reduce losses up to 1.87 MW.

Page 4 of 9 | Total Record : 83

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