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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 24 Documents
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Search results for , issue "Vol 9, No 1: March 2021" : 24 Documents clear
Engineering factors as a decision model for choosing the type of renewable energy power plant establishment in Thailand Songkrit Trerutpicharn; Waranon Kongsong; Kijbodi Kongbenjapuch
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 9, No 1: March 2021
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v9i1.2722

Abstract

The objective of this article is to propose the approach about engineering factors as a decision model for choosing the type of renewable energy power plant establishment in Thailand with supporting information to increase the number of renewable energy power plant establishments. Reducing energy consumption through the government and energy development from renewable energy plays an important role to strengthen the energy security for the country by increasing economic stability. To conserve the environment and reduce the use of energy from fossils, which is one of the main causes of global warming, the literature about acceptance, consisting of attitude related to usage, performance expectations, expectations of use, social influence, environmental support and government policy with analysis of decision models including interest in products, desire for products, product knowledge and the possibility to buy in the future to create energy security for the country, was reviewed. The government is making an effort to encourage the private sector to install electricity generation systems using renewable energy with support in various fields, including tax measures and the providing of various benefits to create investment incentives, such as academic information support, import duty exemption on raw materials for solar panels, support with funding loans, and revolving funds through financial institutions.
Design and Simulation of Modular Multilevel Converter Fed Induction Motor Drive Ahmed Kamil Hannan; Turki K Hassan
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 9, No 1: March 2021
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v9i1.2699

Abstract

Traditional modular multilevel converter (MMC) applications in medium voltage induction motor drive are difficult, particularly at low speeds because of the higher magnitude of the voltage ripple of the sub-module capacitor. This paper uses a hybrid MMC, particularly at low frequencies, to achieve a lower peak-to-peak voltage ripple of the sub-module capacitor. The vector control strategy with the closed-loop speed control indicates an accurate and wide-speed range. MATLAB / Simulink is used to simulate and obtain the simulation results of hybrid and traditional MMC with induction motor drive and compare from the standpoint of capacitor voltage ripple. The results are shown the reduction of peak-to-peak voltage ripple of the sub-module capacitor as the hybrid MMC is operated.
Design of the Digital I/O Pad Buffer for Mixed-Voltage Application Said El Mouzouade; Karim El khadiri; Zakia Lakhliai; Ahmed Tahiri
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 9, No 1: March 2021
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v9i1.1706

Abstract

A new circuit design of digital bidirectional input/output (I/O) pad buffer for mixed voltage is presented. The digictal bidirectional I/0 buffer is designed to avoid reflections by matching the output impedance to the 50 ohms of the transmission line and having overshoots and undershoots below 300mV by increasing the output impedance. The digital bidirectional I/O pad buffer provides minimum delays between input and output and minimum rising and falling times. The proposed digital bidirectional I/O pad buffer was designed, simulated and layouted in Cadence using in TSMC  0.18um CMOS process with a linear resistive element electrically connected at an I/O pad for limiting a processed data I/O signal. The output rising time and falling time are 0.42 ns and 0.93 ns with 3pF load respectively. The final chip area is only 5 um2 .
A Context-Aware Mobile-Based System for Crime Prevention and Emergencies Sarifah Putri Raflesia; Taufiqurrahman Taufiqurrahman; Dinda Lestarini; Ali Bardadi
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 9, No 1: March 2021
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v9i1.2624

Abstract

Crime is a global issue that arises as a consequence of social problems in society such as poverty and densely population due to urbanization. In large cities, governments have applied technology to support crime prevention. In this paper, a mobile-based system is proposed to increase knowledge and public awareness which may reduce the risk of crimes. A context-aware system, namely, geo-fence, is used to enable virtual fences around crime hotspots. Crime hotspots are determined using crime histories and crowd-sourced data provided by citizens. As citizens enter crime hotspots, they would be alerted and provided information. Meanwhile, if they find or experience crime, they are able to report and label the location of the crime.
Noise reduction system by using CNN deep learning model Haengwoo Lee
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 9, No 1: March 2021
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v9i1.2494

Abstract

In this paper, we propose a new algorithm to reduce the acoustic noise of hearing aids. This algorithm improves the noise reduction performance by the deep learning algorithm using the neural network adaptive prediction filter instead of the existing adaptive filter. The speech is estimated from a single input speech signal containing noise using a 80-neuron, 16-filter convolutional neural network(CNN) filter and an error backpropagation algorithm. This is by using the quasi-periodic property of the voiced section in the speech signal, and it is possible to predict the speech more effectively by applying the repeated pitch. In order to verify the performance of the noise reduction system proposed in this research, a simulation program using Tensorflow and Keras libraries was coded and a simulation was done. As a result of the experiment, the proposed deep learning model improves the mean square error(MSE) of 28.5% compared to using the existing adaptive filter and 17.2% compared to using the FNN(full-connected neural network) filter.
Classification and Grip of Occluded Objects Robinson Jimenez-Moreno; Paula Useche-Murillo
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 9, No 1: March 2021
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v9i1.1846

Abstract

The present paper exposes a system for detection, classification, and grip of occluded objects by machine vision, artificial intelligence, and an anthropomorphic robot, to generate a solution for the subjection of elements that present occlusions. The deep learning algorithm used is based on Convolutional Neural Networks (CNN), specifically Fast R-CNN (Fast Region-Based CNN) and DAG-CNN (Directed Acyclic Graph CNN) for pattern recognition, the three-dimensional information of the environment was collected through Kinect V1, and tests simulations by the tool VRML. A sequence of detection, classification, and grip was programmed to determine which elements present occlusions and which type of tool generates the occlusion. According to the user's requirements, the desired elements are delivered (occluded or not), and the unwanted elements are removed. It was possible to develop a program with 88.89% accuracy in gripping and delivering occluded objects using networks Fast R-CNN and DAG-CNN with achieving of 70.9% and 96.2% accuracy respectively, detecting elements without occlusions for the first net and classifying the objects into five tools (Scalpel, Scissor, Screwdriver, Spanner, and Pliers), with the second net. The grip of occluded objects requires accurate detection of the element located at the top of the pile of objects to remove it without affecting the rest of the environment. Additionally, the detection process requires that a part of the occluded tool be visible to determine the existence of occlusions in the stack
Design and Implementation of Multiplexed and Obfuscated Physical Unclonable Function Mohd Syafiq Mispan; Hafez Sarkawi; Aiman Zakwan Jidin; Radi Husin Ramlee; Haslinah Mohd Nasir
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 9, No 1: March 2021
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v9i1.2664

Abstract

Model building attack on Physical Unclonable Functions (PUFs) by using machine learning (ML) techniques has been a focus in the PUF research area. PUF is a hardware security primitive which can extract unique hardware characteristics (i.e., device-specific) by exploiting the intrinsic manufacturing process variations during integrated circuit (IC) fabrication. The nature of the manufacturing process variations which is random and complex makes a PUF realistically and physically impossible to clone atom-by-atom. Nevertheless, its function is vulnerable to model-building attacks by using ML techniques. Arbiter-PUF is one of the earliest proposed delay-based PUFs which is vulnerable to ML-attack. In the past, several techniques have been proposed to increase its resiliency, but often has to sacrifice the reproducibility of the Arbiter-PUF response. In this paper, we propose a new derivative of Arbiter-PUF which is called Mixed Arbiter-PUF (MA-PUF). Four Arbiter-PUFs are combined and their outputs are multiplexed to generate the final response. We show that MA-PUF has good properties of uniqueness, reliability, and uniformity. Moreover, the resilient of MA-PUF against ML-attack is 15% better than a conventional Arbiter-PUF. The predictability of MA-PUF close to 65% could be achieved when combining with challenge permutation technique.
A Mini Review of Peer-to-Peer (P2P) for Vehicular Communication Sumendra Yogarayan; Siti Fatimah Abdul Razak; Afizan Azman; Mohd. Fikri Azli Abdullah
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 9, No 1: March 2021
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v9i1.2736

Abstract

In recent times, peer-to-peer (P2P) has evolved, where it leverages the capability to scale compared to server-based networks. Consequently, P2P has appeared to be the future distributed systems in emerging several applications. P2P is actually a disruptive technology for setting up applications that scale to numerous concurrent individuals. Thus, in a P2P distributed system, individuals become themselves as peers through contributing, sharing, and managing the resources in a network. In this paper, P2P for vehicular communication is explored. A comprehensive of the functioning concept of both P2P along with vehicular communication is examined. In addition, the advantages are furthermore conversed for a far better understanding on the implementation.
Design and Analysis of a Broadband Microwave Amplifier Obinna Okoyeigbo; Augustus E Ibhaze; Ayobami Olajube; Olamilekan Shobayo; Tobiloba Somefun; Onyinyechi Steve-Essi
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 9, No 1: March 2021
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v9i1.2708

Abstract

This paper presents the procedures involved in the design and analysis of a microstrip broadband microwave amplifier. For system design, simulation, optimization and analysis, a Computer Aided Design (CAD) tool know as Agilent Advanced Design System (ADS) was employed. The amplifier device- FLC317MG-4 FET, was tested for stability, and was observed to be unconditionally stable between 2 to 6 GHz frequency band. Two possible ideal matching circuits were investigated to identify the best matching circuit with the maximum transducer power gain. It was observed that the quarter-wave transformer with parallel open circuit stub, gave a high gain at a wider range of frequency (larger bandwidth/ broadband), than the other matching circuit. Hence, it was employed for the broadband amplifier design using microstrips, and achieved a maximum flat gain of about 9.8 dB to 10.118 dB, at a bandwidth of 3.5 to 4.5 GHz.
Mini Kirsch Edge Detection and Its Sharpening Effect Joyce Sin Yin Sia; Tian Swee Tan; Azli Bin Yahya; Matthias Foh Thye Tiong; Jeremy Yik Xian Sia
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 9, No 1: March 2021
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v9i1.2597

Abstract

In computer vision, edge detection is a crucial step in identifying the objects’ boundaries in an image. The existing edge detection methods function in either spatial domain or frequency domain, fail to outline the high continuity boundaries of the objects. In this work, we modified four-directional mini Kirsch edge detection kernels which enable full directional edge detection. We also introduced the novel involvement of the proposed method in image sharpening by adding the resulting edge map onto the original input image to enhance the edge details in the image. From the edge detection performance tests, our proposed method acquired the highest true edge pixels and true non-edge pixels detection, yielding the highest accuracy among all the comparing methods. Moreover, the sharpening effect offered by our proposed framework could achieve a more favorable visual appearance with a competitive score of peak signal-to-noise ratio and structural similarity index value compared to the most widely used unsharp masking and Laplacian of Gaussian sharpening methods.  The edges of the sharpened image are further enhanced could potentially contribute to better boundary tracking and higher segmentation accuracy.

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