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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
 731   732   733   734   735 
A new motion structure for a six-legged insect robot with Bluetooth remote-control Mazin Abdulelah Alawan; Ali Kadhim Abdulabbas; Oday Jasim Mohammed Al-Furaiji
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp760-769

Abstract

This paper focuses on motion which is considered an important issue for insect robots, which consumes significant energy sources in general. We inspired the robot design structure from the challenges that crawling insects face in nature, especially a cockroach. The proposed robot configuration enhanced error scale such as energy modulation, computation, and mass. This paper presents the design and construction of six-legged robot with minimum number of trigger motors and the movement mechanisms used for the leg movements. The insect robot resembles a cockroach in shape and size (1.6 cm × 4 cm) and can move at rates of up to 3.5 cm per second. The robot can operate for up to 260 minutes. Additionally, it has a camera that can rotate more than 60 degrees in response to commands from a smartphone. The 160×120 pixels monochrome "first person" camera transmits video to a Bluetooth radio at a distance of up to 120 meters away at a frame rate of 1 to 5 per second.
Covariance absolute values spectrum sensing method based on two adaptive thresholds Bushra T. Hashim; Hadi T. Ziboon; Sinan M. Abdulsatar
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp1029-1037

Abstract

Cognitive radio is a modern wireless communication methodology that deals with the issue of spectrum untapped. Cognitive users can continually perceive the licensed spectrum to hunt for unoccupied spots. The essential technology in cognitive radio (CR) for primary user detection is spectrum sensing. Due to signal to noise ratio (SNR), noise uncertainty in spectrum sensing would make the detection unreliable. In this paper, the two adaptive thresholds based on_covariance absolute values (TATCAV) are proposed to increase detection performance in the presence of noise uncertainty. According to the computer simulations using MATLAB 2021b, the value of the probability of detection is Pd=98.1% Compared with the results of two thresholds based on_covariance absolute values (TTCAV) Pd= 95.3% at SNR=-18, noise uncertainty Nu=1.761 dB, and using quadrature amplitude modulation (QAM). And the error rate for the proposed approach is Pe=12.1% under the same circumstances. The proposed approach results, according to the simulations, are considerably better than the results of the fixed two-threshold approach.
Hermitan matrices based malicious cognitive radio detection and bayesian method for detecting primary user emulation attack Devasahayam Joseph Jeyakumar; Boominathan Shanmathi; Parappurathu Bahulayan Smitha; Sekar Vinurajkumar; Mohanan Murali; Muthuraj Mariselvam
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp956-964

Abstract

Cognitive radio (CR) is a facilitating technology to efficiently deal with the spectrum scarceness, and it will significantly enhance the spectrum deployment of upcoming wireless transmission method. Security is a significant concern, although not well tackle in cognitive radio networks (CRN). In CR networks, this approach regard as a security issue happen from primary user emulation attack (PUEA). A PUEA attacker forwards an emulated primary signal and defraud the CR users to avoid them from accessing spectrum holes. Here, we introduce a Hermitan matrices based malicious cognitive radio (CMCR) detection and Bayesian method for detecting PUEA attack in the CRN. In this approach, the Bayesian method is used for detecting the PUEA attack. The trust analyzer evaluates the CR trust. Here, the node trust value is computed by node activeness and inactiveness, degree of data transmission, and hermitan matrics verification. In addition, the Hermitan Matrices method is used to detect the malicious CR user in the CRN. The simulation outcomes propose that the CMCR leads to improve the performance in terms of better detection ratio, minimized the possibility of miss detection ratio. Furthermore, it minimized the possibility of false alarm in the CRN.
Machine learning to improve the performance of anomaly-based network intrusion detection in big data Siriporn Chimphlee; Witcha Chimphlee
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp1106-1119

Abstract

With the rapid growth of digital technology communications are overwhelmed by network data traffic. The demand for the internet is growing every day in today's cyber world, raising concerns about network security. Big Data are a term that describes a vast volume of complicated data that is critical for evaluating network patterns and determining what has occurred in the network. Therefore, detecting attacks in a large network is challenging. Intrusion detection system (IDS) is a promising cybersecurity research field. In this paper, we proposed an efficient classification scheme for IDS, which is divided into two procedures, on the CSE-CIC-IDS-2018 dataset, data pre-processing techniques including under-sampling, feature selection, and classifier algorithms were used to assess and decide the best performing model to classify invaders. We have implemented and compared seven classifier machine learning algorithms with various criteria. This work explored the application of the random forest (RF) for feature selection in conjunction with machine learning (ML) techniques including linear regression (LR), k-Nearest Neighbor (k-NN), classification and regression trees (CART), Bayes, RF, multi layer perceptron (MLP), and XGBoost in order to implement IDSS. The experimental results show that the MLP algorithm in the most successful with best performance with evaluation matrix.
Supply chain strategy during the COVID-19 terms: sentiment analysis and knowledge discovery through text mining Muhammad Khahfi Zuhanda; Yuan Anisa; Desniarti Desniarti; Muhammad Hafiz; Anil Hakim Syofra; Rezzy Eko Caraka; Maengseok Noh
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp1120-1127

Abstract

The coronavirus pandemic has affected not only health but also the economy. The use of big data in finding information can be used to gain profits that logistics companies can utilize to survive during the pandemic. This study conducted text-mining research on service consultant sites in the logistics sector. This study aims to present frequency diagrams, analyze sentiment using the National Research Council (NRC) lexicon, present bigrams, and seek knowledge about strategies to minimize shipping costs and maintain inventories of manufactured goods. The words "supply", "chain", and "COVID-19" are words that are used frequently throughout the article. The results of this study showed that the words that often appear from word excavation are the words "supply", "chain", "logistics", "kpis," and "inventory". Then emotion trust becomes an emotional word that often appears in articles. The words "Supply" and "pandemic" are the words that seem the most positive and negative words, respectively. The words "COVID-19", "safety stock", and "inventory management" are words that often appear together. The result of discovery knowledge is that logistics consultants offer emotions of trust and provide many insights on minimizing shipping costs and maintaining inventory during a pandemic.
Rainfall prediction model in Semarang City using machine learning Carissa Devina Usman; Aris Puji Widodo; Kusworo Adi; Rahmat Gernowo
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp1224-1231

Abstract

The erratic distribution of rainfall greatly affects people's daily activities, especially in Semarang City, so it is necessary to predict rainfall. Correct prediction of rainfall can improve community preparedness in dealing with natural disasters. Algorithms for machine learning and data mining have been extensively utilized in research involving rainfall data from various regions. The primary objectives of this study are to find the best regression algorithm and use machine learning algorithms to predict rainfall in Semarang. The dataset used is daily rainfall data for the City of Semarang from the meteorological, climatological, and geophysical agency (BMKG). Machine learning algorithms such as multiple linear regression, random forest regression, and replicated neural networks will be used to conduct regression analysis on this dataset. The mean absolute error and Root mean squared error techniques are utilized to evaluate the performance of machine learning algorithms. With an error rate of 13.055 for root mean squared error (RMSE) and 6.621 for mean absolute error (MAE), the results of the research indicate that the performance of the neural network algorithm is superior to that of other algorithms.
Effects of (Ba,Ca)ScO2F:Bi3+,K+ phosphor particle size on color uniformity white light-emitting diodes Ha Thanh Tung; Huu Phuc Dang
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp707-713

Abstract

Phosphors that offer considerable performance as well as heat consistency has been a high priority of recent studies concerning light-emitting diodes (LED) devices. This study employs the perovskite phosphors BCSOF (short for Ba1-xCaxScO2F:0.001Bi3+,0.001K+ with x value from 0 to 0.12 and one chip at 415 nm generating thin green illumination via cation-replacement method. The study examines the aftermath when Ca2+ replaces Ba2+ within the crystal formations of BCSOF as well as the luminescent features of the phosphors, detecting a formation of cube-like perovskite within the space group of Pm3m in the employed phosphors. In addition, the study also assesses the development concerning the magnitude of cells as well as the binding extent of Ba/Ca/K/Bi-O. When the inner quantum performance reaches 77.4% in BCSOF, a potent green discharge is manifested, reaching 510 nm when excited by a chip at 415 nm. Greater luminescent performance as well as heat consistency correlating with changes in inner formation were reported. Via the method of replacing cations, it is possible to control spectrum by manipulating the latticework’s surroundings, leading to desirable performance in LED products.
Transmission line characterization and modeling for electronic circuits and systems design Oluwole John Famoriji; Thokozani Shongwe
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp730-738

Abstract

Channel bandwidth-limited high-speed links or interfaces make circuit solutions not efficient. Both recent and subsequent links (SerDes-Serializer/Deserializer) design demand efficient and effective coupling between future circuit design, communication, and optimization. The challenges vary and new solutions are needed. In this article, an analytical wireline model is presented to predict electronic path loss towards adequate designs of electronic circuits and systems. An open loop system analysis is adapted in this paper. Our model was tested against different channels: a legacy channel with via stub discontinuity and FR4 dielectric, and a more recent microwave-engineered channel without stub and NELCO 6,000 dielectric, a very good matching attained. Good agreement was observed between our model and electromagnetic full-wave simulation data, as a result showed high level of applicability to thin-film microstrip line for adequate circuit design. The model is recommended for electronic engineers for adequate and faster interfaces and high-speed links designs.
The impacts from SrS:Cu+,Na and LaOF:Eu3+ phosphors on color and luminous performances at 5600 K–8000 K WLEDs Ha Thanh Tung; Huu Phuc Dang
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp714-720

Abstract

In terms of lumen performance, the remote phosphor structure can yield better results than the conformal phosphor and in-cup phosphor packages. The application of such a package in LEDs might make the manipulation of the device’s chromatic performance challenging. Two remote phosphor packages are available for raising chromatic performance: one-layer and triple-layer phosphor adjustments. Using software simulation and phosphors created through specific procedures, our study was carried out to select the best adjustment that provides the best results in white LEDs (WLEDs) implemented with many chips: color rendering index (CRI), color quality scale (CQS), lumen output (LO), along with chromatic uniformity. We utilized the WLEDs at five temperatures of color between 5,600 K and 8,500 K. From the outcome, we can consider the three-layer phosphor package to have greater CRI, CQS, and lumen efficiency (LE). Notably, CQS and LE receive a roughly 30% boost compared to singular-layer package. The package can also reduce the chromatic deviation by roughly 30% to 50%, and therefore, grants a boost in chromatic homogeneity. To authenticate these outcomes, the dispersion attribute underwent examination in the layers of phosphor based on Mie-dispersion hypothesis. The outcome may prove useful for creating WLED devices with greater standards.
Raga classification using enhanced spatial bound whale optimization algorithm Bettadamadahally Shivakumaraswamy Gowrishankar; Nagappa U. Bhajantri
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp825-837

Abstract

A raga is a unique set of notes with certain rules that carefully followed, retain and protect its purity and produce amazing musical effects. An automated raga transcription and identification is important for computational musicology, which is an important step for musicology for indexing, classifying, and recommending tunes. In the present research, the audio features such as mel frequency cepstrum coefficients (MFCCs), spectral flux, short time energy, audio feature extractor, and spectral centroid features are used for the prediction of a raga. The model showed more complexity which means it required lots of training data. The proposed enhanced spatial bound whale optimization algorithm (ESBWOA) is used that overcome the feature selection problem of high dimensional features. In addition to this, a weighted salp swarm algorithm (SSA) is used for selecting the tone-based features from the ragas based on amplitude or each raga sample. The features were fed for bidirectional long short-term memory (Bi-LSTM) network, which enhanced the success rate for raga identification and classification. The present research uses CompMusic dataset in the research work where 9 classes for Carnatic music and 7 classes in Hindustani music are considered for the classification of ragas.

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