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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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Comparison of DC-DC converters for solar power conversion system Debani Prasad Mishra; Rudranarayan Senapati; Surender Reddy Salkuti
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp648-655

Abstract

This paper covers the comparison between four different DC-DC converters for solar power conversion. The four converters are buck converter, buck-boost converter, boost converter, and noninverting buck-boost converter. An MPPT algorithm is designed to calculate battery voltage, current of PV array, the voltage of PV array, power of PV array, output power. It is observed that the non-inverting buck-boost converter is the finest converter for solar power conversion. The final circuit design has the results of 12.2V battery voltage, 0.31A current of PV array, 34V voltage of PV array, 23mW power of PV panel, and 21.8mW of output power. The efficiency of this system is nearly 95%. All four circuits are simulated in MATLAB/Simulink R2020b.
Orthogonal frequency division multiplexing system with an indexed-pilot channel estimation Ali Alqatawneh
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp808-818

Abstract

In this paper, we examine an orthogonal frequency division multiplexing (OFDM) system under imperfect channel conditions and pilot-insertion- based channel estimation. However, unlike conventional pilot-insertion-based channel estimation, some inserted pilot symbols are set to zero where the index of the zero-pilot symbols is employed to transmit extra data bits. In this paper, we employ a minimum mean squared error (MMSE) to detect transmitted pilot symbols; these symbols are then used to estimate channel coefficients. Furthermore, the impact of zero-pilot symbols on the mean-squared error of channel estimation and on system error performance is examined. Our findings show that the index of zero-pilot symbols can be used to improve system throughput by carrying extra information bits without harming channel estimation accuracy or degrading system error performance. Simulation results show that, at a high signal-to-noise ratio, the bit error rate for data bits transmitted via zero-pilot symbols index selection is lower than that of data bits transmitted over data subcarriers.
Comparative analysis and prediction of coronary heart disease Sashikanta Prusty; Srikanta Patnaik; Sujit Kumar Dash
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 2: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i2.pp944-953

Abstract

Cardiovascular disease (CVD) is now one of the leading causes of death worldwide and was also thought to be a serious illness in the mid and old ages. Artificial intelligence and machine learning have a huge impact on the healthcare areas. As a result, getting a familiar individual with data processing techniques suitable for numerical health data. Although, the most often used algorithms for classification tasks will be incredibly advantageous in terms of time management. In particular here, a common procedure has been proposed for predicting cardiovascular disease. Accordingly, we herein consider nine typical classifiers of both machine learning and deep learning technology for the comparative analysis and prediction of coronary heart failure. These models are computationally inexpensive and easy to build. Moreover, these classifiers are tested and compared using a confusion matrix in the Jupyter notebook, yielding classification measures such as accuracy, f1-score, recall, and precision. As a result, the logistic regression classifier gives the maximum possible accuracy, precision, and f1-score of 90.78%, 90.24%, and 91.35% respectively.
An improved energy management control strategy for a standalone solar photovoltaic/battery system Ouadiâ Chekira; Ali Boharb; Younes Boujoudar; Hassan El Moussaoui; Tijani Lamhamdi; Hassane El Markhi
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 2: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i2.pp647-658

Abstract

This paper proposes efficient energy management in hybrid microgrid-comprising of photovoltaic (PV) and battery storage systems. The proposed technique. The hybrid system's power balance is based on smart control to meet the demands of isolated off-grid direct current (DC) loads as well as to stabilize the voltage to DC Bus. The Perturb and Observe technique (P&O) is used to achieve maximum power point tracking by adjusting the duty cycle of the Bidirectional converter, which links the Li-ion battery to the DC Bus of stand-alone power systems (SPS). The proposed controller regulates the power flow of the battery for efficiency voltage control in a microgrid. The energy management system proposed has been approved using MATLAB/Simulink under variable solar irradiation conditions. The simulation results show that the technique used increases the battery cycle-life and better energy management and voltage control performance compared with previous examples.
Thai digit handwriting image classification with convolutional neural networks Kheamparit Khunratchasana; Tassanan Treenuntharath
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp110-117

Abstract

This paper aims to determine the efficiency in classifying and recognizing Thai digit handwritten using convolutional neural networks (CNN). We created a new dataset called the Thai digit dataset. The performance test was divided into two parts: the first part determines the exact number of epochs, and the second part examines the occurrence of overfits in the model with Keras library's EarlyStoping() function, processed through Cloud Computing with Google Colaboratory, and used a Python programming language. The main parameters for the model were a dropout of 0.75, mini-batch size of 128, the learning rate of 0.0001, and using an Adam optimizer. This study found the model's predictive accuracy was 96.88 and the loss was 0.1075. The results showed that using CNN in image classification and recognition. It has a high level of prediction efficiency. However, the parameters in the model must be adjusted accordingly.
Selection of Gd2(WO4)3:Tb3+ for inproving color deviation in white light-emitting diodes Dieu An Nguyen Thi; Nguyen Doan Quoc Anh; Phan Xuan Le
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 2: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i2.pp709-714

Abstract

This study successfully using the hydrothermal technique to synthesize Gd2(WO4)3:Tb3+ phosphors when subjected to calcination under the temperature of 900°C. Here are some aspects that were thoroughly examined: the crystal formation, photoluminescence, photoluminescence excitation, as well as fluorescent degradation for the samples. The (Gd2-xTbx)(WO4)3 (x=0.01-0.15) phosphors exhibit a bright discharge of green under 547 nm (5D4→7F5 shift for Tb3+) when excited at 270 nm (4f8→4f75d1 shift for Tb3+). Because of the exchange interaction between Tb3+, the quenching concentration was determined to be around 10%. The addition of Tb3+ had no effect on the (Gd2-xTbx)(WO4)3 phosphors' CIE chromaticity coordinates (~0.33±0.02, ~0.60±0.02) or color temperatures (~5542 K). Nevertheless, when the Tb3+ content increased, the fluorescence lifespan for 547 nm emission reduced due to energy transfer between Tb3+. The strong green emission from Gd2(WO4)3:Tb3+ phosphors is a potential element for WLEDs and display areas.
Performance evaluation of unmanned aerial vehicle communication by increasing antennas of cellular base stations Rajesh Kapoor; Aasheesh Shukla; Vishal Goyal
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp222-237

Abstract

The utilization of unmanned aerial vehicles (UAVs) increases with increased performance of their communication link with the ground remote station. Integrating UAVs with existing cellular networks provides the possibility of enhanced performance of communication links. The base stations of existing cellular networks are installed with fixed number of antennas. The performance of UAV communication links can be further enhanced by increasing antennas of cellular base stations of existing networks using multiple antenna techniques such as multi ple input multiple output (MIMO). In this proposed scheme, Massive MIMO technology is used for UAV communications, wherein hundreds of antennas are mounted on cellular base stations. This set up provides significant advantage in terms of enhancement in per formance of UAV communication links, as compared to existing methods of UAV communication. In this paper, performance evaluation of UAV communication links is carried out by increasing the number of antennas at base stations of existing cellular networks. For this evaluation, firstly basic multiple antennas techniques such as point - to - point MIMO and multi - user MIMO (MU - MIMO) are covered based on existing studies and findings. Subsequently, an antenna dependent closed form expression for uplink channel capac ity of massive MIMO based UAV communication links is derived, with few numerical results.
High performance time series models using auto autoregressive integrated moving average Redha Ali Al-Qazzaz; Suhad A. Yousif
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp422-430

Abstract

Forecasting techniques have received considerable interest from both researchers and academics because of the unique characteristics of businesses and their influence on several areas of the economy. Most academics utilize the autoregressive integrated mov ing average (ARIMA) approach to forecasting the future. However, researchers face challenges, such as analyzing the data and selecting the appropriate ARIMA parameters, especially with large datasets. This study investigates the use of the automatic ARIMA (Auto ARIMA) function for forecasting Brent oil prices. It demonstrates the benefits of using Auto ARIMA over ARIMA for determining the appropriate ARIMA parameters based on measures such as root mean square error ( RMSE ) , mean absolute error ( MAE ) , and aka ike information criterion ( AIC ) without requiring the attention of an expert data scientist as it bypasses several steps needed for manual ARIMA. Auto ARIMA produced an RMSE of 12.5539 and an AIC of 1877.224, which are comparable to the values resulting fr om the manual ARIMA with the help of expert data scientists; thus, it saves analysis time and offers the best model result.
Quadratic vector support machine algorithm, applied to prediction of university student satisfaction Omar Chamorro-Atalaya; Guillermo Morales-Romero; Yeferzon Meza-Chaupis; Elizabeth Auqui-Ramos; Jesús Ramos-Cruz; César León-Velarde; Irma Aybar-Bellido
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp139-148

Abstract

This study aims to identify the most optimal supervised learning algorithm to be applied to the prediction of satisfaction of university students. In this study, the IBM SPSS - 25.0 software was used to test the reliability of the satisfaction questionnaire and the MATLAB R2021b software through the classification learner technique to determine the supervised learning algorithm. The experimental results determine a Cronbach's Alpha reliability of 0.979, in terms of the classification algorithm, it is validate d that the quadratic vector support machine (SVM) has better performance metrics, being correct in 97.8% (a ccuracy) in the predictions of satisfaction of university students, with a r ecall (sensitivity) of 96.5% and an F1 score of 0.968. Likewise, when eva luating the classification model by means of the receiver operating characteristic curve (ROC) technique, it is identified that for the three expected classes of satisfaction the value of the area under the curve (AUC) is equal to 1, in such sense the pred ictive model through the SVM Quadratic algorithm, has a high capacity to distinguish between the 3 classes ; i) d issatisfied, ii) s atisfied and iii) v ery satisfied of satisfaction of university students.
An asymmetric encryption method for 3D mesh model using elgamal with elliptic curve cryptography Pongpisit Wuttidittachotti; Pornsak Preelakha
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 2: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i2.pp959-969

Abstract

The 3D mesh (Polygon mesh) model has been widely used in multiple computer technology fields such as computer graphic design and modern 3D animation. 3D mesh repositories were created to support the contribution of many 3D artist-designers and have become an important data source. This research is aimed at introducing asymmetric encryption for a 3D mesh model to improve encryption using elgamal elliptic curve cryptography with Fischer-Yates shuffling. The researchers evaluated the performance of the proposed model using Entropy, mean squared error (MSE), and peak signal noise ratio (PSNR) as evaluation matrices. The results of a decrypted model using our approach with a double-precision floating point showed zero means squared error and infinite value of PSNR.

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