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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
Arjuna Subject : -
Articles 64 Documents
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Search results for , issue "Vol 29, No 1: January 2023" : 64 Documents clear
Digital forensics on Tencent QQ-instant messaging service in China Yunkun Li; Gabriela Mogos
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp412-420

Abstract

Data packet analysis targeting instant messaging (IM) applications has become one of the most mentioned case examples in the digital forensic industry, considering that the forensic engineers can extract valuable information by analysing the data packets used by the IM software. The crucial part of this process is to accomplish a series of research and investigation, in addition to correctly implement the related forensics tools. This paper is intended to use QQ, a popular IM software in China, as an experiment example, in cooperation with various tools from Kali Linux, a digital forensics-oriented Linux distribution, to present the complete process of the data packet analysis operation. The result concludes from the experiment may be able to provide constructive suggestions to other related digital forensics cases.
Unified power quality control based microgrid for power quality enhancement using various controlling techniques Mythreyee Madhavan; Nalini Anandan
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp75-84

Abstract

This research analyses the introduction of unified power quality control (UPQC) to mitigate the power quality problems, which is caused by using power electronics devices. In this article, the challenges in power quality, the suggested UPQC control approaches that are made by the distributed generation of dynamic voltage restorer (DVR) and static synchronous compensator (STATCOM) with the DC-link. The DVR is a series active power filter (APF) compensator and the STATCOM is a shunt APF compensator. In the meanwhile, DVR compensates voltage related issuesas well as STATCOM provides the needed reactive power supply by load and reducing the current issues associated with the unity power factor. The main objectives of the UPQC to mitigate voltage imbalance, harmonics, negative-sequence current and reactive power. To overcome the PQ issues the multifunction power conditioner is implemented. In addition, several proposed control approaches were employed and compared with series and shunt APFs. In MATLAB/Simulink software is used to illuminate the performance of the control strategies. Finally, the simulation will be evaluated and PQ problems in UPQC will be reduced by various techniques such as unit vector template generation technique (UVTGT), power balancing theory (BPT), proportional integral (PI) control technique and hysteresis control technique.
Editorial cloud collaborative service improves authorized industrial server database performance Eswara Narayanan; Balasundaram Muthukumar
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp441-450

Abstract

The E-commerce platform for the automotive industry has various obstacles regarding product distribution and sales marketing. Problems such as identifying the product's low defect rate and mapping failure features to the product's existing quality set, both of which occur in the actual world, are included in this category. With the help of an editorial cloud collaborative service, this study will focus primarily on identifying the core causes of product failure. The machine learning confidential (MLC) protocol is used to authenticate the editor's identity when accessing the industrial server's database. A cloud-based collaborative editing service can also be used to extract the root cause of a specific problem from customer complaints. There may be some product flaws that can be remedied with extra features gathered from the end-user to understand real-world practicality better and ensure product accuracy reaches 100% target.
Analysis the efficiency of multi-input-multi-output (MIMO) transmit receive systems Ali Hlal Mutlaq; Mohammed Ayad Saad; Faris Hassan Tata; Ghanim Thiab Hasan
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp190-196

Abstract

Transmit antennas are chosen in multi-input-multi-output (MIMO) systems. Effective in improving system capacity while lowering RF connection costs and simplifying the system. Complete method with greatest accuracy for joint transmits and receive antenna selection (JTRAS), capable of scanning all subsets of both transmitting and receiving antennas for the optimal solution. However, when as the number of antennas but also computational complexity increase grows too great, limiting its application. Antennas are coded fractionally channel capacity maximizing coding is used as a basic criterion in this paper, and an intelligent algorithm Particle swarm algorithm, generic algorithm are used to pick antennas. The simulation results show that both algorithms are capable of performing antenna selection.
Boxplot analysis of 4 grade agarwood essential oil for various grades Anis Hazirah 'Izzati Hasnu Al-Hadi; Aqib Fawwaz Mohd Amidon; Siti Mariatul Hazwa Mohd Huzir; Nurlaila Ismail; Zakiah Mohd Yusoff; Saiful Nizam Tajuddin; Mohd Nasir Taib
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp238-244

Abstract

Agarwood essential oil is used in most perfumery ingredients, as an incense and in traditional medical preparations. Agarwood essential oil, called "Black Gold," is extremely valued to the global community due to its numerous benefits. As of now, there is still no standard technique of grading different grades of agarwood essential oil. The current grading technique is inefficient since the agarwood essential oil is graded by using human sensory panel. Different people might have different perspective on grading the agarwood essential oil hence, the technique is not practical to adapt it globally. Due to the current technology, numerous intelligent techniques for verifying the grades of agarwood essential oil have been proposed and implemented. The study has conducted a statistical analysis on 4 grade agarwood essential oil using boxplot. Boxplot analysis summarizes the abundances for each chemical compounds from four different grades of agarwood essential oil with a high grade as a reference. This study shows the analysis of boxplot investigated 10-epi-δ-eudesmol, α-agarofuran, β-agarofuran, δ-eudesmol and dihydrocollumellarin as most important chemical compounds in high grade of agarwood essential oil. The chemical compounds that have been identified in high grade of agarwood essential oil can be a reference for future research studies.
Hide text in an image using Blowfish algorithm and development of least significant bit technique Sarah Kareem Salim; Mohammed Majid Msallam; Huda Ismail Olewi
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp339-347

Abstract

Recently, there is increasing interest in data transfer between many different devices. Data must be encrypted before being sent so that the intended receiver can only read it to prevent unauthorized access and processing of a secret message. This paper suggests two levels of security to secure import messages that are sent via the internet. A secret text is encrypted by a Blowfish algorithm, then the secret text is hidden in an image by the least significant bit (LSB) technique. The LSB method of concealing important information was developed to conceal at least the first of at least two bits, depending on the cover data. The resolution of an image is raised in our work where the sender selects a stego image with a high peak signal to noise ratio (PSNR). The receiver knows all the necessary information for decoding by the first nine pixels. The PSNR is used for evaluating the resolution of the image to check robustness at sending. The number of PSNR illustrates in our proposal that the resolution of the image is near the original LSB technique, but the embedding is more randomly robust in steganography.
Comparative analysis and feature importance of machine learning and deep learning for heart disease prediction Priyanka Gupta; Dambarudhar Seth
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp451-459

Abstract

Cardiovascular disease (CVD) or heart disease is one of the main reasons for early death, even at young age and that too often sudden. If it is detected more accurately, much before it seriously affects the individual, life can be saved through proper medication and changes in lifestyles. In this work different machine learning classifiers and a deep learning algorithm multi-layer perceptron (MLP) were applied on two different datasets, Framingham heart study dataset and UCI heart disease dataset for prediction of heart disease. These algorithms were optimized using hyperparameter tuning and compared for their performance measures and prediction accuracies. For different features, feature importance scores were calculated using machine learning algorithms. The features were ranked according to their scores. Out of various classification algorithms, random forest algorithm has shown the best results with prediction accuracy of 97.13% for Framingham dataset. MLP has shown good performance for both the datasets.
Shooting swarm algorithm for solving two-point boundary value problems Suhaib Abduljabbar Altamir; Mohammed Abdulrazaq Kahya; Azzam Salahuddin Younus Aladool
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp553-561

Abstract

Boundary value problems (BVPs) are solved using the more detailed swarm algorithm (SA) based on particle swarm optimization (PSO) and firefly algorithm (FA). In the field of optimization techniques, both PSO and FA have good features to solve many problems in applied mathematics. Due to the sensitivity of the use of the controversial shooting method for solving BVPs, which can not able to reach the exact solution oftentimes. A shooting Swarm algorithm (SSA) is proposed based on PSO and FA. Several BVPs including stiff BVPs were principally used to investigate the SSA. The numerical experiments and analyses revealed that the algorithm was able to overcome the shooing method drawbacks. On another hand, the proposed method that is based on FA significantly reduces the number of iterations required for solving BVPs, because of its flexible properties in the exploration and exploitation phases, and it is in good agreement with the exact solution of BVPs. The SSA was investigated to solve stiff BVPs and Its efficacy has been proven with the accurate solutions.
Osteoporosis detection using convolutional neural network based on dual-energy X-ray absorptiometry images Abulkareem Z. Mohammed; Loay E. George
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp315-321

Abstract

Osteoporosis is one of the most common diseases that affect the bones of adults, especially women in menopause, and the reason for this is due to the lack of bone mineral density bone mineral density (BMD). BMD can be measured by X-ray and dual energy X-ray absorptiometry (DEXA) images, this article, focused on using DEXA images for Osteoporosis detection. At first, the original image must passed through the preprocessing stage, during which the noisy parts is reduced, and the useless parts are eliminated, and then the contrast between adjacent areas is increased and the area of interest is allocated. After that, the image is passed in a deep learning model in order to extract the unique features on the basis of which each image is classified. The classification result was excellent with 98% accuracy. The used dataset is “Osteoporosis DEXA scans images” of Spine from Pakistan.
Performance improvement of visible light communication links based on coded unipolar OFDM Wasnaa N. Al-Musawi; Hassan K. Al-Musawi
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp217-224

Abstract

Visible light communications are limited by the narrow bandwidth of their sources as the light-emitting diodes, which restricts the high data rates transmission. A potential technique such as multi-carrier modulation is considered promising for achieving a high-speed data rate and enhancing system performance. This paper proposes turbo coding with unipolar orthogonal frequency-division multiplexing (U-OFDM) for indoor environments. The system under U-OFDM considerations can reduce the inter-symbol interference caused by multiple paths and mitigate burst errors by adopting an iterative turbo decoding. The system performance is evaluated regarding the bit error rate (BER) for the range of the signal-to-noise ratio (SNR) under receiver field-of-view (FOV) restriction. The obtained results show that the performance system of the target BER (below the threshold limit of 3.8×10−3) has a power penalty of ~9 dB for modulation order of 64 for quadrature amplitude modulation scheme, FOV of 50°, and incidence angle of half power assigned to 30°. The obtained results also showed a ~10.8 dB improvement in the SNR when comparing the present system with coded-DC-biased optical OFDM under the same considerations.

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