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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 9,174 Documents
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Data storage model in low-cost mobile applications I Made Sukarsa; I Kadek Ari Melinia Antara; Putu Wira Buana; I Putu Agung Bayupati; Ni Wayan Wisswani; Dina Wahyuni Puteri
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 2: November 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i2.pp1128-1138

Abstract

Mobile applications that have data transactions between users require a database relational database management system (RDBMS) and RESTful API operating on the hosting service so that all users can access the data. Renting a hosting service is not cheap and creating a RESTful API takes plenty of time. As an alternative to hosting, a free version of the Cloud Firestore service gives full access rights to the database and has an application programming interface (API) to manage data or access data. However, the free version of Cloud Firestore has limitations in terms of storage capacity, read, write, and delete processes. Therefore, redesigning process of the database was carried out into a low-cost version of the database model consisting of SQLite database and a low-cost version of the NoSQL database to overcome this problem. The goal is to reduce storage space usage and read, write, and delete processing on Cloud Firestore. The low-cost version of the database was tested with 6,030 data. The results obtained were savings of 47.27% storage usage, 83.08% write usage, 91.26% read process usage, and 83.19% delete process usage compared to the test results of the relational database model.
Alzheimer’s disease prediction using three machine learning methods Shaymaa Taha Ahmed; Suhad Malallah Kadhem
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1689-1697

Abstract

Alzheimer's disease (AD) is the most common incurable neurodegenerative illness, a term that encompasses memory loss as well as other cognitive abilities. The purpose of the study is using precise early-stage gene expression data from blood generated from a clinical Alzheimer's dataset, the goal was to construct a classification model that might predict the early stages of Alzheimer's disease. Using information gain (IG), a selection of characteristics was chosen to provide substantial information for distinguishing between normal control (NC) and early-stage AD participants. The data was divided into various sizes; three distinct machine learning (ML) algorithms were used to generate the classification models: support vector machine (SVM), Naïve Bayes (NB), and k-nearest neighbors (K-NN). Using the WEKA software tool and a variety of model performance measures, the capacity of the algorithms to effectively predict cognitive impairment status was compared and tested. The current findings reveal that an SVM-based classification model can accurately differentiate cognitively impaired Alzheimer's patients from normal healthy people with 96.6% accuracy. As discovered and validated a gene expression pattern in the blood that accurately distinguishes Alzheimer's patients and cognitively healthy controls, demonstrating that changes specific to AD can be detected far from the disease's core site.
Photovoltaic system DC series arc fault: a case study Alaa Hamza Omran; Dalila Mat Said; Siti Maherah Hussin; Sadiq H. Abdulhussain
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 2: November 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i2.pp625-635

Abstract

Photovoltaic (PV) systems are becoming increasingly popular; however, arc faults on the direct current (DC) side are becoming more widespread as a result of the effects of aging as well as the trend toward higher DC voltage levels, posing severe risk to human safety and system stability. The parallel arc faults present higher level of current as compared with the series arc faults, making it more difficult to spot the series arc. In this paper and for the aim of condition monitoring, the features of a DC series arc fault are analyzed by analysing the arc features, performing model’s simulation in PSCAD, and carrying out experimental studies. Various arc models are simulated and investigated; for low current arcs, the heuristic model is used where a set of parameters established. Moreover, the heuristic model’s simulated arc has been shown to be compatible with the experimental data. The features of arc noise in the electrode separation region and steady-arcing states with varied gap widths are investigated. It has been discovered that after an arc fault occurs, arc noise increases, notably in the frequency range below 50 kHz; where this property is useful for detecting DC series arc faults. Besides that, variations in air gap width are more sensitive to frequencies under 5 kHz.
Design of traveling wave slotted waveguide array antenna with high efficiency Najat Shyaa Jasim Mohammed; Manal Hadi Jaber
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1496-1501

Abstract

The slotted waveguide antenna is one of the most important antennas used in high-frequency applications, in radars, navigation systems, remote sensing systems and communications because of its efficiency and high gains. In this paper, the slotted waveguide antenna was designed and simulated with suitable specifications with a working frequency range of 2-2.45 where this antenna was checked by plotting S parameters in the designed frequency band and we got a very good reflection coefficient for the designed antenna (S11) at the operating frequency, draw and illustrate the three-dimensional radiation pattern of the designed antenna that shows the gain and bandwidth at the operating frequency. The performance of a 9-element slotted waveguide array antenna with an operating frequency of up to 12 GHz was also investigated by plotting the S11 parameters and illustrating the designed antenna directivity diagram.We obtained the reflection coefficient of the designed array antenna (S11) below -23 dB at the operating frequency, and the SWG antenna directivity pattern with a maximum value of=13.2 dB and a minimum value of=-23 dB.
Large dataset partitioning using ensemble partition-based clustering with majority voting technique Vunnava Dinesh Babu; Karunakaran Malathi
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 2: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i2.pp838-844

Abstract

Large datasets have become useful in data mining for processing, storing, and handling vast amounts of data. However, handling and processing large datasets is time-consuming and memory intensive. As a result, the researchers adopted a partitioning strategy to improve controllability and performance and reduce the time and memory required to handle large datasets. Unfortunately, the numerous clustering techniques available in the literature could confuse experts in choosing the best techniques for a given dataset. Furthermore, no clustering technique can tackle all problems, such as cluster structure, noise, or density. To manage large datasets, existing clustering techniques need scalable solutions. Therefore, this paper proposes an ensemble partition-based clustering with a majority voting technique for large dataset partitioning using the aggregation of k-means, k-medoids, fuzzy c-means, expectation-maximization (EM) and density-based spatial clustering of applications with noise (DBSCAN) techniques. These techniques cluster the large dataset individually in the first stage. The final clusters are discovered in the next stage through a majority voting technique among the five clustering algorithms. These five clustering algorithms assigned data instances to the cluster with the most votes. The experimental findings demonstrate that the ensemble partition-based clustering method surpasses the other five clustering algorithms in terms of execution time and accuracy.
Elimination of ferroresonance in the distribution zone by high ohmic reactor-shunt limiter Alaa M. Abdel-hamed; Mohamed M. EL-Shafhy; Ebrahim A. Badran
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 3: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i3.pp1286-1296

Abstract

Electrical network components catastrophically fail as a result of aberrant system oscillations. Also, consequently leads to saturation in the ferromagnetic core elements. These factors induce distortions in the voltage and current waveforms as well as a large rise in voltage or current. This paper presents the role of distributed generation (DG) in contributing to ferroresonance investigation reduction in the distribution sector. A high ohmic reactor-shunt limiter (HOR-SL) is introduced as a novel technique based on a negative sequence component to mitigate ferroresonance. The proposed HOR-SL reduces the ferroresonance in distribution system (DS) by no more than 10.5 msec. A PSCAD/EMTDC software is used to model the ferroresonance phenomenon. The simulation results strongly show the effectiveness of using the proposed HOR-SL for limiting ferroresonant oscillations and creating stable orbit in the distribution sector. Case studies verified the effectiveness of the proposed technique in mitigating ferroresonance oscillations and keeping the security of the distribution zone.
Remote laser welding simulation for aluminium alloy manufacturing using computational fluid dynamics model Raghad Ahmed Al-Aloosi; Zainab Abdul-Kareem Farhan; Ahmad H. Sabry
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1533-1541

Abstract

The process of remote laser welding is simulated in this study to identify the keyhole-induced porosity generation mechanisms and keyhole. Three processes are simulated and discussed: laser power levels, laser-beam shaping configurations, and laser keyhole process. The simulation finding reveals that pore development is caused by strong melt flow behind the keyhole. As verification, the equivalent experimental test is also carried out. According to the findings, a welding speed with a high level helps to keep the keyholes released and prevents the flow of strong melt; a big advanced leaning-angle also provides inactive molten pool flow, making it difficult for bubbles to float to the backside of the molten pool. The conclusions of this study offer crucial insight into the method of porosity of aluminum (Al) alloys laser welding, as well as advice on how to avoid keyhole-induced porosity. It is also obtained that a smaller laser beam with constant power raises the velocity, welding pool depth, and liquid metal temperature.
Healthcare assessment for beauty centers using hybrid sentiment analysis Abeer Khalid Al-Mashhadany; Ahmed T. Sadiq; Sura Mazin Ali; Amjed Abbas Ahmed
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 2: November 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i2.pp890-897

Abstract

Because of COVID-19, healthcare became the first interesting domain at the world. Here, comes the role of researchers to do what they can to guide people. Nowadays, the most wanted field is beauty industry. It achieved large market. And the estimation is toward the growing. Researchers can give advice to prevent unhealthy causes in this field. They can apply sentiment analysis methods to make decision whether a Beauty center is healthy or unhealthy. This work develops an improved method of sentiment analysis to classify the beauty centers in Iraq into healthy and unhealthy classes. Researchers used comments of beauty centers’ Facebooks to perform the assessment. The methodologies encompass the two approaches lexicon-based and machine-learning-based. Three machine learning mechanisms had been applied; rough set theory, naïve bayes, and k-nearest neighbors. It will be shown that rough set theory is the best compared with the others two. Rough set theory achieved 95.2%, while Naïve Bayes achieved 87.5% and k-nearest neighbors achieved 78%.
Construct an efficient distributed denial of service attack detection system based on data mining techniques Dhurgham Kareem Gharkan; Amer A. Abdulrahman
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.pp591-597

Abstract

Distributed denial-of-service (DDoS) attack is bluster to network security that purpose at exhausted the networks with malicious traffic. Although several techniques have been designed for DDoS attack detection, intrusion detection system (IDS) It has a great role in protecting the network system and has the ability to collect and analyze data from various network sources to discover any unauthorized access. The goal of IDS is to detect malicious traffic and defend the system against any fraudulent activity or illegal traffic. Therefore, IDS monitors outgoing and incoming network traffic. This paper contains a based intrusion detection system for DDoS attack, and has the ability to detect the attack intelligently, dynamically and periodically by evaluating the set of attackers of the current node with its neighbors. We use dataset named CICDDoS2019 that contains on binary classes benign and DDoS. Performance has evaluated by applying data mining algorithms as well as applying the best features to discover potential attack classes.
A marine thruster’s model identification based on experimental-simulation approach Abdelmalek Laidani; Mohamed Bouhamida; Zakaria Bellahcene
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 3: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i3.pp1414-1424

Abstract

In recent years, underwater vehicles play a very important role in the marine field, and tasks cannot be accomplished quickly and accurately without the use of such devices. Despite the progress achieved, these vehicles still have prob- lems with their controls in order to have a very good dynamic positioning or a path tracking accurately, and these problems have a direct link to their thrusters, either by negligence or by ignorance of its mathematical model. Several works were carried out to have an accurate model of them, but its behavior is still diffi- cult to be described and it strongly influences the behavior of a vehicle in which it is integrated. In this work we try to deal this problem in the aim to iden- tify a marine thruster designed by us using a low-cost test bench and a hybrid identification approach, which combines the both experimental and simulation parts. The thruster will be integrated on a remotely operated vehicle under devel- opment by AVCIS-Lab to make simulation using UUV (unmanned underwater vehicle) Simulator and ROS (Robot Operating System) toolbox under Matlab. The outcomes will be presented at the end of this paper.

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