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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 10 Documents
 1 
Search results for , issue "Vol. 2 No. 2 (2024)" : 10 Documents clear
Technical Analysis Using 100 Percent Palm Kernel Shell as Fuel in Circulation Fluidized Bed Boiler Type Masrajuddin; Sudiarto, Budi; Setiabudy, Rudy
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.v2i2.44

Abstract

Energy is a basic human need that has increased in use. Given the limited energy resources, it is necessary to manage energy appropriately and efficiently. Energy efficiency not only has an impact on reducing production costs, but also on reducing emissions. As a concrete step to support the government's net zero emission program by 2060, the company is trying to use alternative biomass fuels, namely: palm kernel shell. The purpose of this study is to conduct a technical and economic analysis of the use of 100 percent palm kernel shells as fuel in a circulation fluidized bed boiler type power plant. This research was conducted at power plant unit 2 of PT XYZ, located in Cilegon, Banten Province. The parameters measured are limited to boiler efficiency, thermal efficiency, and heat rate. The results showed that when using palm kernel shells, boiler efficiency decreased 0.47 percent, thermal efficiency decreased 0.24 percent, and heat rate increased 22 kcal/kWh or 0.76 percent. By considering of three operational parameters (boiler efficiency, thermal efficiency, and heat rate) it can be concluded that technically the use of 100 percent palm kernel shells as fuel in the plant is feasible. There is no major impact on boiler performance regarding the transition of coal to palm kernel shells. The impact of long-term use of palm kernel shells on equipment is beyond the scope of this research.
IoT-Based Vehicle Monitoring System on LoRa Network: Addressing Community Needs in Indonesia Zulkifli, Fitri Yuli; Halimsurya, Ervin; Ayyasy, Muhammad; Luthfi, Fitya; Alinursafa, Ibnu
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.v2i2.46

Abstract

Our innovative IoT-based vehicle monitoring system emerges from a comprehensive survey among vehicle owners. The device circuit is designed using ESP32, GPS to detect location and speed, MPU6050 to detect vibrations from the vehicle engine, and a relay that is used to disconnect the vehicle socket if needed. The data collected from each component is sent through the LoRa Antares network. Access to the data can be done using a cell phone through the MOTRAV application that has been integrated with the Antares server. The designed system is able to display the location, speed, and condition of the vehicle consistently with an average delay of 7 seconds and can receive 65% of the control signals to start and stop the vehicle engine. The system can also send a warning notification if the vehicle that is not being used is detected at a speed of more than 5.5 km/h with engine vibrations detected reaching 28 vibrations/5 seconds.
Analysis of an Integrated QEEG-Neurofeedback System Utilizing Active Stimuli for Non-Pharmacological Intervention in Enhancing Neurobehavioral Function Mahatidana, Pradipta; Musridharta, Eka; Basari
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.v2i2.47

Abstract

Quantitative Electroencephalogram (QEEG) and Neurofeedback (NF) are employed in the diagnosis and treatment of neurobehavioral deficits associated with various clinical conditions. These approaches enable the exploration of EEG usage within the context of neurobehavioral electrophysiology. This study aims to elucidate the fundamental evidence supporting NF and to outline strategies for its further development and application in ameliorating neurobehavioral deficits. Numerous research studies have demonstrated the efficacy of NF in enhancing neurobehavioral functions, including attention, language, memory, visuospatial abilities, and executive function. This study intends to develop an NF system that includes the establishment of a robust approach to QEEG transformation and database. The closed-loop QEEG-NF system under development incorporates active visual and auditory stimuli that leverage stochastic phenomena. The efficacy of the QEEG NF treatment was confirmed with a statistically significant increase in alpha brain wave percentages post-treatment (p = 0.018), indicating that the system effectively enhances alpha brain wave production.
Transmission Outage Cost Analysis Using Value of Loss Load Approach Based on Macro Economic Data Suwargono, Son; Garniwa, Iwa
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.v2i2.48

Abstract

The West Nusa Tenggara (NTB) electricity system, which consists of the Lombok System and the Sumbawa-Bima System, has an important role in supporting the country's economy, especially in the tourism segment. Quantitatively, there has been no measurement of the impact of electricity disruption on the macro economy. Value of Loss Load (VoLL) is a useful quantity parameter in the economic evaluation of electric power systems. It can be represented as the value of losses borne by customers in case of electricity service interruptions. For policy makers and electricity management, the size of the VoLL would affect decisions regarding investment. A low VoLL requires for a low reliability level and a high VoLL for a high reliability level. This research will calculate Transmission outage costs using the Value of Loss Load approach based on macro economic data and predicting VoLL 2024 - 2030. The outcome of the research shows that The Lombok System VoLL is lower than Bima – Sumbawa System. Outage costs due to disruptions on the Transmission System side affect GDP by 0.001% / year. The trend of VoLL 2024 – 2030 is estimated to decrease by an average of 2.29% / year which is indicate it is is inline with Rencana Usaha Penyediaan Tenaga Listrik 2021 - 2030.
Performance Evaluation Elastic Security as Open Source Endpoint Detection and Response for Advanced Persistent Threat Cyberattack Putra, Zegar Pradipta; Harwahyu, Ruki; Hebert, Evans
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.v2i2.49

Abstract

Detecting APT using conventional information protection systems poses significant challenges. For instance, signature-based detection tools like antivirus primarily rely on predefined signature rules to identify malware. However, in scenarios like zero-day attacks where malware signatures are unknown, detection becomes unreliable. While EDR traditionally hinges on signature-based rules, recent advancements integrate machine learning techniques for enhanced detection capabilities. In this study, we conducted an evaluation of open-source EDR, specifically Elastic Security, for APT detection. APT attack vectors were simulated utilizing the Caldera Platform. The evaluation involved validating each attack vector sent by Caldera against detection alerts generated by Elastic Security. The detection outcomes revealed three categories: detected alerts conforming to predefined rules, undetected alerts despite predefined rules, and undetected alerts due to undefined rules. Some attack vectors lacked rule definitions, potentially resulting in elevated false positives. Additionally, certain attack vectors failed to trigger alerts despite rule definitions.
Energy Management System using Evolutionary Mating Algorithms for Optimizing Energy Usage and User Comfort in Office Building Alvin, Bob; Husnayain, Faiz; Sudiarto, Budi; Setiabudy, Rudy
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.v2i2.50

Abstract

Indonesia has set a target to reduce emissions by 29% or 835 million tons of CO2 by 2030, which was increased to 32% or 912 million tons of CO2 in 2023. The building sector is one of the largest contributors to emissions in Indonesia. To reduce these emissions, the Indonesian government has issued energy conservation regulations requiring each sector to reduce energy consumption. According to Government Regulation No. 33 of 2023, energy conservation is mandatory for energy users in the building sector who use energy sources equivalent to or greater than 500 Tons of Oil Equivalent. One way to conserve energy is by implementing energy-efficient technologies, without compromising the comfort of building users, which includes thermal and visual comfort as part of indoor environmental quality (IEQ). An energy-efficient technology using the Evolution Mating Algorithm (EMA) is proposed. This study will discuss energy use without compromising building user comfort in tropical countries using the EMA optimization algorithm. The study demonstrates that EMA successfully optimizes energy use without reducing user comfort in tropical countries.
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.
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.

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