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INDONESIA
Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
Published by IAES Indonesia Section and Partners
ISSN : 20893272     EISSN : -     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) is a peer reviewed International Journal in English published four issues per year (March, June, September and December). The aim of Indonesian Journal of Electrical Engineering and Informatics (IJEEI) is to publish high-quality articles dedicated to all aspects of the latest outstanding developments in the field of electrical engineering. Its scope encompasses the engineering of Telecommunication and Information Technology, Applied Computing & Computer, Instrumentation & Control, Electrical (Power), Electronics, and Informatics.
Arjuna Subject : -
Articles 783 Documents
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Smart System Side Slip Tester Results Accuracy Improvement Using Exponential Filter Arief Marwanto; Riky Maulana Firdaus; Muhammad Qomaruddin; Deshinta Arrova Dewi; Tri Basuki Kurniawan; Imam Much Ibnu Subroto
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 2: June 2023
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v11i2.3576

Abstract

According to Article 6, Paragraph 1, of Law No. 55 of 2012 Concerning Cars, cars that are not roadworthy are particularly harmful for the safety of passengers and other road users. The front wheel ring, which has a significant impact on the safety of the motorized vehicle, is one of the technical requirements for roadworthiness. The front wheel pins make sure the car can go straight, which is related to the steering system's safety and has an impact on fuel economy. Through routine testing at the motor vehicle testing facility owned by the Transportation Service, the front wheel valve examination is performed using a front wheel blade test tool known as the Side Slip Tester. Previously, a lot of the automobile test equipment used at various test facilities was impractical and inaccurate. The construction of a smart system for evaluating wheel blades on cars is covered in this study, along with the implementation of an exponential filter to improve and lower the noise in sensor readings of ADC signals. By comparing the readings of the manufactured tool with a calibrated dial indicator, tests and calibrations are performed. The graph shows that the response to the input signal is quick and excellent for noise filtering, so based on the results of the exponential filter test, 0.2 is the ideal weight for the ADC reading filter. The 9 mm side slip bench shear test yields a maximum error result of 3% following tool calibration.
Malware Detection Approaches Based on Operation Codes (OpCodes) of Executable Programs: A Review Mohammed A. Saleh
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 2: June 2023
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v11i2.4454

Abstract

A malicious software, or Malware for a short, poses a threat to computer systems, which need to be analyzed, detected, and eliminated. Generally, malware is analyzed in two ways: dynamic malware analysis and static malware analysis. The former collects features dataset during running of the malware, and involves malware APIs, registry activities, file activities, process activities, and network activities based features. The latter collects features dataset prior and without running the malware, and involves Operational Codes (OpCodes) and text based (Bytecodes) features. However, several previous researchers addressed and reviewed malware detection approaches based on various aspects, but none of them addressed and reviewed the approaches merely based on malware OpCodes. Therefore, this paper aims to review Malware Detection Approaches based on OpCodes. The review explores, demonstrates, and compares the existing approaches for detecting malware according to their OpCodes only, and finally presents a comprehensive comparable envisage about them.
An Enhanced Cluster-Based Routing Model for Energy-Efficient Wireless Sensor Networks Rotimi Alagbe Gbadebo; Mistura Laide Sanni; Bodunde Odunola Akinyemi; Temitope Omotosho Ajayi; Ganiyu Adesola Aderounmu
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 2: June 2023
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v11i2.4566

Abstract

Energy efficiency is a crucial consideration in wireless sensor networks since the sensor nodes are resource-constrained, and this limited resource, if not optimally utilized, may disrupt the entire network's operations. The network must ensure that the limited energy resources are used as effectively as possible to allow for longer-term operation. The study designed and simulated an improved Genetic Algorithm-Based Energy-Efficient Routing (GABEER) algorithm to combat the issue of energy depletion in wireless sensor networks. The GABEER algorithm was designed using the Free Space Path Loss Model to determine each node's location in the sensor field according to its proximity to the base station (sink) and the First-Order Radio Energy Model to measure the energy depletion of each node to obtain the residual energy. The GABEER algorithm was coded in the C++ programming language, and the wireless sensor network was simulated using Network Simulator 3 (NS-3). The outcomes of the simulation revealed that the GABEER algorithm has the capability of increasing the performance of sensor network operations with respect to lifetime and stability period.
Optimal Control Technique of an Induction Motor Cheikh Oudaa; Ethmane Isselem Arbih Mahmoud; Abdel Kader Kader Mahmoud; Cherif Bilal Djamal Eddine; Bendiabdellah Azeddine
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 2: June 2023
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v11i2.4447

Abstract

The squirrel cage induction motor (IM) has many advantages over other types of electric technique (FOC), classical direct torque control (DTC), and direct torque control with space vector modulation (DTC-SVM) is carried out. The objective of this paper is to decouple the mechanical quantities such as torque and flux in a way similar to the DC motor control. And also to minimize the torque and flux modulation of the IM. Torque oscillations can cause mechanical resonances and consequently acoustic noise, hence damaging the machine. Reducing the switching frequency significantly minimizes switching losses. The DTC-SVM control technique improves the performance of conventional DTC, which is characterized by low torque and flux modulation as well as a fixed switching frequency. Simulation results in MATLAB show that torque and current ripples are reduced with the improved DTC. DTC-SVM used for the traction control system is easy to implement in digital systems and also allows to move the photovoltaic panels according to the position of maximum sunshine to extract the maximum energy with high efficiency from the system.
A Review of Energy Management of Renewable Multisources in Industrial Microgrids Walter Naranjo Lourido; Fredy A. Sanz; Javier Eduardo Martinez Baquero
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 3: September 2023
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v11i3.4530

Abstract

This review aims to consolidate recent advancements in power control within microgrids and multi-microgrids. It specifically focuses on analyzing the comparative benefits of various architectures concerning energy sharing and demand cost management. The paper provides a comprehensive technical analysis of different architectures found in existing literature, which are designed for energy management and demand cost optimization. In summary, this review paper provides a thorough examination of power control in microgrids and multi-microgrids and compares different architectural approaches for energy management and demand cost optimization.
Optimized Reversible Logic Multiplexer Designs for Energy-Efficient Nanoscale Computing C.Vijesh Joe; Haewon Byeon; Anand Kumar Singh; C. Ramesh Kumar; Aaquil Bunglowala; Anu Tonk
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 3: September 2023
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v11i3.4367

Abstract

Nano- and quantum-based low-power applications are where reversible logic really shines. By using digitally equivalent circuits with reversible logic gates, energy savings may be achieved. Reducing garbage output and ancilla inputs is a primary emphasis of this study, which aims to lower power consumption in reversible multiplexers. Multiplexers with switchable 2:1, 4:1, and 8:1 ratios may be built using the SJ gate and other simple reversible logic gates. The number of ancilla inputs has been cut in half from four to zero, and the amount of garbage output has been cut in half as well, from eight to three, making the 2:1 multiplexer an improvement over the prior design. New 4:1 multiplexer has 10' ancilla inputs, up from 2' in the previous designs. The proposed 4:1 multiplexer also cuts waste production in half from the current 5-to-6 bins per day. The 8:1 multiplexer has two ancilla inputs and nine trash outputs, while the current architecture only has one of each. The functionality of the VHDL and Xilinx 14.7-coded designs is validated by ISIM simulations.
Predictive-TOPSIS-based MPPT for PEMFC Featuring Switching Frequency Reduction Jye Yun Fam; Shen Yuong Wong; Mohammad Omar Abdullah; Kasumawati Lias; Saad Mekhilef; Hazrul Mohamed Basri
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 3: September 2023
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v11i3.4350

Abstract

A maximum power point tracking (MPPT) for a proton exchange membrane fuel cell (PEMFC) using a combination of conventional finite control set model predictive control (FCS-MPC) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is proposed in this paper. The key idea is to maximize the power generation from a PEMFC while minimizing the switching frequency of the power converter. The FCS-MPC technique is formulated to track the maximum power of PEMFC highly affected by ever-changing internal parameters. Meanwhile, the TOPSIS algorithm is applied to overcome the potential weaknesses of insulated-gate bipolar transistor (IGBT), which can only withstand a lower switching frequency. In this project, all simulations were run using MATLAB software to display the output power of the PEMFC system. As a result, the proposed predictive-TOPSIS-based MPPT algorithm can track the MPP for various PEMFC parameters within 0.019 s with an excellent accuracy up to 99.11%. The proposed MPPT technique has fast-tracking of the MPP locus, excellent accuracy, and robustness to environmental changes.
Detecting Urban Road Changes using Segmentation and Vector Analysis M. Sobhana; Gudapati Satya Dinesh Kumar; Yarramreddy Tejaswi; Pavithra Pakkiru
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 3: September 2023
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v11i3.4662

Abstract

The rapid growth of urbanization is driving increased road infrastructure development. Detecting and monitoring changes in urban road areas is challenging for city planners. This research proposes using semantic segmentation and vector analysis on high-resolution images to identify road network changes. The U-Net model performs semantic segmentation, pre-trained on a Massachusetts road dataset, predicting labels for a specific area with temporal data and co-registration to reduce distortions. Predicted labels are converted to shapefiles for vector analysis. Satellite images from Google Earth archives demonstrate the change detection process. The outcome of this predictive phase was the transformation of projected labels into shapefiles, thereby facilitating vector analysis to pinpoint and characterize alterations.
Voltage Instability and Voltage Regulating Distribution Transformer Assessment Under Renewable Energy Penetration For Low Voltage Distribution System Nur Syazana Izzati Razali; Teddy Surya Gunawan; Siti Hajar Yusoff; Mohamed Hadi Habaebi; Saerahany Legori Ibrahim; Siti Nadiah Mohd Sapihie
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 3: September 2023
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v11i3.4857

Abstract

The Voltage Regulating Distribution Transformer (VRDT) is a tap-changing transformer that regulates the voltage across all three phases. However, its application in the context of renewable energy penetration into low-voltage grids remains understudied. This paper addresses this research gap by presenting a refined voltage drop model tailored for the International Islamic University Malaysia (IIUM) distribution network. Based on a derived mathematical equation, the model is validated and analyzed using Simulink's modeling platform. Simulations are performed without and with the VRDT, revealing that renewable energy penetration can cause instability, leading to voltage deviations proportional to the injected renewable energy. Incorporating the VRDT in the low-voltage grid allows for voltage adjustment under loaded conditions, ensuring uninterrupted renewable energy injection. Voltage stability analysis is conducted using actual load consumption data from the IIUM network for 2020 and 2021, offering valuable insights despite assuming equal energy consumption across buildings. Most hostels exhibit stable distribution systems with solar energy, but instability arises when solar energy comprises 100% of the input for the Safiyyah and Zubair hostels' 11kV distribution transformers. Implementing the VRDT regulates this instability, restoring system stability. This study highlights the importance of VRDT integration in high renewable energy proportion low-voltage grids, enabling voltage regulation and stability under variable renewable energy injection scenarios. The findings demonstrate that VRDTs mitigate voltage instability caused by renewable energy, providing a reliable solution for incorporating renewables into low-voltage distribution networks. It contributes to understanding renewable energy's impact on distribution system stability and offers guidance for VRDT implementation in similar contexts. 
Implementation of Supervised Machine Learning on Embedded Raspberry Pi System to Recognize Hand Motion as Preliminary Study for Smart Prosthetic Hand Triwiyanto Triwiyanto; Sari Luthfiyah; Wahyu Caesarendra; Abdussalam Ali Ahmed
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 3: September 2023
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v11i3.4397

Abstract

EMG signals have random, non-linear, and non-stationary characteristics that require the selection of the suitable feature extraction and classifier for application to prosthetic hands based on EMG pattern recognition. This research aims to implement EMG pattern recognition on an embedded Raspberry Pi system to recognize hand motion as a preliminary study for a smart prosthetic hand. The contribution of this research is that the time domain feature extraction model and classifier machine can be implemented into the Raspberry Pi embedded system. In addition, the machine learning training and evaluation process is carried out online on the Raspberry Pi system. The online training process is carried out by integrating EMG data acquisition hardware devices, time domain features, classifiers, and motor control on embedded machine learning using Python programming. This study involved ten respondents in good health. EMG signals are collected at two lead flexor carpi radialis and extensor digitorum muscles. EMG signals are extracted using time domain features (TDF) mean absolute value (MAV), root mean square (RMS), variance (VAR) using a window length of 100 ms. Supervised machine learning decision tree (DT), support vector machine (SVM), and k-nearest neighbor (KNN) are chosen because they have a simple algorithm structure and less computation. Finally, the TDF and classifier are embedded in the Raspberry Pi 3 Model B+ microcomputer. Experimental results show that the highest accuracy is obtained in the open class, 97.03%. Furthermore, the additional datasets show a significant difference in accuracy (p-value <0.05). Based on the evaluation results obtained, the embedded system can be implemented for prosthetic hands based on EMG pattern recognition.

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