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Bulletin of Electrical Engineering and Informatics
Published by Universitas Ahmad Dahlan
ISSN : -     EISSN : -     DOI : -
Core Subject : Engineering,
Electrical & Electronics Engineering
Bulletin of Electrical Engineering and Informatics (Buletin Teknik Elektro dan Informatika) ISSN: 2089-3191, e-ISSN: 2302-9285 is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world. The journal publishes original papers in the field of electrical, computer and informatics engineering.
Arjuna Subject : -
Articles 2,901 Documents
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Structured query language query join optimization by using rademacher averages and mapreduce algorithms Chandrashekariah, Yathish Aradhya Bandur; H. A., Dinesha
Bulletin of Electrical Engineering and Informatics Vol 13, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i3.6837

Abstract

Query optimization involves identifying and implementing the most effective and efficient methods and strategies to enhance the performance of queries. This is achieved by intelligently utilizing system resources and considering various performance metrics. Table joining optimization involves optimizing the process of combining two or more tables within a database. Structured query language (SQL) optimization is the progress of utilizing SQL queries in the possible way to achieve fast and accurate database results. SQL optimization is critical to decreasing the no of queries in research description framework (RDF) and the time for processing a huge number of relatable data. In this paper, four new algorithms are proposed such as hash-join, sort-merge, rademacher averages and mapreduce for the progress of SQL query join optimization. The proposed model is evaluated and tested using waterloo sparql diversity test suite (WatDiv) and lehigh university benchmark (LUBM) benchmark datasets in terms of time execution. The results represented that the proposed method achieved an enhanced performance of less execution time for various queries such as Q3 of 5362, Q8 of 5921, Q9 of 5854 and Q10 of 5691 milliseconds. The proposed gives better performance than other existing methods like hybrid database-map reduction system (AQUA+) and join query processing (JQPro).
Numerical simulation of one-dimensional perovskite solar cell model Aisyahtun Sakinah, Saidatul Nur; Ranom, Rahifa; Basmin, Siti Hajar; Jin Yao, Lee
Bulletin of Electrical Engineering and Informatics Vol 13, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i4.6463

Abstract

Perovskite solar cell (PSC) is one of the advanced third-generation solar cells that have rapid efficiencies but instability issues in terms of air, moisture, and UV light sensitivity becomes a barrier to commercialization. The instability issue is due to the charge accumulation at the interface of the PSC reducing its efficiency. This research focuses on the operation of PSCs through a one-dimensional (1D) drift-diffusion model for planar heterojunction PSCs. The model also accounts for the electric potential by Poisson’s equation, the ion generation, and the recombination rate. The method of lines technique is applied to solve the model for the perovskite layer numerically using the finite difference method which is then solved forward in time using the ‘ode15s’ solver in MATLAB. It is highlighted that the comparison with the experimental data from the reference shows good agreement. The effect of parameter thickness variation of the perovskite layer upon the efficiency of PSCs is analyzed. The result shows that the best efficiency obtained is 19.77% obtained at thickness 0.25 ??. The results may prove useful for a guideline of the cell thickness that predicts the perovskites cell performance.
Experimental study the performance of a 6-bladed Savonius vertical axis wind turbine using polyvinyl chloride material Siregar, Izhary; Dwi Nugroho, Setyawan; Zaskia Pratiwi, Citra; Mawardi, Iman; Jibril, Ahmad; Suhadi, Suhadi
Bulletin of Electrical Engineering and Informatics Vol 13, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i6.7550

Abstract

The Savonius U type wind turbine is a vertical axis turbine that can operate at low wind speeds. In general, the performance of this turbine is influenced by several factors, one of which is the shape of the turbine blade. This research aims to test the design results of a 6 blade Savonius turbine with a blade length of 50 cm made from polyvinyl chloride (PVC) by varying the dimensions of the blade diameter. The variables that vary between blade length and blade diameter are D/L=0.10, D/L=0.13, D/L=0.18, and D/L=0.20. The aim of this research is to determine the effect of variations in the parameters above on turbine rotation and the electrical power produced in a direct current (DC) generator at each variation in wind speed. From the research results, it is known that the trend graph of the relationship between turbine rotation and wind speed has a linear correlation. In simple terms, this turbine can be applied to DC voltage loads such as lighting using light emitting diode (LED) lamps with a maximum power capacity of ± 16 watts, while the overall efficiency (OE) is 50.25%.
Feature importance for software development effort estimation using multi level ensemble approaches Rao, K. Eswara; Vital Terlapu, Pandu Ranga; Annan Naidu, Paidi; Ravi Kumar, Tammineni; Murali Pydi, Bala
Bulletin of Electrical Engineering and Informatics Vol 13, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i2.5531

Abstract

Feature importance strategy that substantially impacts software development effort estimation (SDEE) can help lower the dimensionality of dataset size. SDEE models developed to estimate effort, time, and wealth required to accomplish a software product on a limited budget are used more frequently by project managers as decision-support tool effort estimation algorithms trained on a dataset containing essential elements to improve their estimation accuracy. Earlier research worked on creating and testing various estimation methods to get accurate. On the other hand, ensemble produces superior prediction accuracy than single approaches. Therefore, this study aims to identify, develop, and deploy an ensemble approach feasible and practical for forecasting software development activities with limited time and minimum effort. This paper proposed a collaborative system containing a multi-level ensemble approach. The first level grabs the optimal features by adopting boosting techniques that impact the decided target; this subset features forward to the second level developed by a stacked ensemble to compute the product development effort concerning lines of code (LOC) and actual. The proposed model yields high accuracy and is more accurate than distinct models.
Elitism-crossover barnacle mating optimization and its application to PID controller design for a buck converter Kasruddin Nasir, Ahmad Nor; Ahmad, Mohd Redzuan; Anwari Roslan, Muhammad Almaa
Bulletin of Electrical Engineering and Informatics Vol 13, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i2.5481

Abstract

This paper presents an elitism-crossover barnacle mating optimization (ECBMO). It is an improvement of barnacle mating optimization (BMO). The original BMO suffers from local optima problem leading to a low accurate solution. A new method of offspring generation is adopted into the original BMO structure. Some features of the best-so-far solution are incorporated into the generated offspring. The accuracy performance of the proposed algorithm is tested on several IEEE functions. A statistical analysis is conducted to compare its performance over the original BMO. It is also applied to optimize proportional integral derivative (PID) parameters for controlling output voltage of a buck converter. Result of benchmark functions test shows the proposed algorithm has attained higher accuracy for all functions compared to BMO algorithm. Application on the real problem shows both algorithms control the converter voltage satisfactorily. However, the ECBMO has achieved more optimal PID parameters and leading to a better output voltage response.
A common vocabulary for semantic interoperability of Moroccan e-government services Laaz, Naziha; Benaddi, Hanane
Bulletin of Electrical Engineering and Informatics Vol 14, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i1.7450

Abstract

Interoperability is a critical factor for the success of e-government services, as it enables different public information systems to communicate in a consistent and accurate manner. Governments are making significant efforts to improve their public e- services interactions and promote e-government interoperability. Morocco has developed an e-government interoperability framework that lists compliance rules and references for the development of public information systems. Unfortunately, Moroccan public administrations still work independently and operate as siloed organizations. To deal with this problem, it is essential to implement a common vocabulary (CV) for public services that public administrations can share to formalize public data, enhance exchange between information systems, and ensure data interoperability. In this light, this work presents a CV to standardize public services data, define concepts and relationships. The standardized vocabulary is defined using RDF/XML serialization format and incorporates fundamental declarations to ensure digital communication in Moroccan public services. The approach is illustrated through a case study of e-health service. The study shows the potential added value of creating a national vocabulary. It helps public administrations to structure data, interoperate more effectively and accelerate digital transformation.
Fuzzy logic method for making push notifications on monitoring system of IoT-based electric truck charging Al Madani Kurniawan, Aqsha; Khaula Amifia, Lora; Iskandar Riansyah, Moch.; Furizal, Furizal; Suwarno, Iswanto; Ma’arif, Alfian; Maghfiroh, Hari
Bulletin of Electrical Engineering and Informatics Vol 14, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i1.7412

Abstract

To minimize the negligence when charging electric vehicles, it is deemed important to have an internet of things (IoT) based monitoring system using a notification feature. The monitoring system of electric vehicle battery charging used a voltage divider and temperature sensor (DS18B20) installed on the Arduino Mega 2560 microcontroller with the addition of an ESP8266 Wi-Fi module for sending microcontroller data into the Blynk platform. A notification feature was added as the reminder that the battery has been overcharging or overheating. This study applied the Mamdani fuzzy logic method to determine the conditions when notifications must appear. The results of the application of the Mamdani fuzzy logic method were able to determine the conditions for push notifications to appear using the parameters as desired; by so doing, it is possible to create a battery monitoring system with accurate push notification feature to prevent the battery from being overcharged and overheated.
Exploring Bengali speech for gender classification: machine learning and deep learning approaches Dewan Arpita, Habiba; Al Ryan, Abdullah; Fahad Hossain, Md.; Sadekur Rahman, Md.; Sajjad, Md; Noor Islam Prova, Nuzhat
Bulletin of Electrical Engineering and Informatics Vol 14, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i1.8146

Abstract

Speech enables clear and powerful idea transmission. The human voice, rich in tone and emotion, holds unique beauty and significance in daily life. Vocal pitches vary by gender and are influenced by emotions and languages. While people naturally perceive these nuances, machines often struggle to capture these subtle distinctions. Machines may struggle to detect these nuances, but people effortlessly perceive them. This project aims to use various machine learning (ML) and deep learning (DL) techniques to reliably determine an individual’s gender from a corpus of Bengali conversations. Our dataset comprises 3185 Bengali speeches, with 1100 delivered by males, 1035 by women, and 1050 by those who identify as third gender. We employed six distinct feature extraction techniques to examine the audio data: roll-off, spectral centroid, chroma-stft, spectral bandwidth, zero crossing rate, and Mel-frequency cepstral coefficients (MFCC). Extreme gradient boosting (XGBoost), support vector machines (SVM), K-nearest neighbors (KNN), decision trees classifier (DTC), and random forest (RF) were employed as the five ML algorithms to comprehensively analyze the dataset. For a full study, we also included 1D convolutional neural networks (CNN) from the DL area. The 1D CNN performed extraordinarily well, exceeding the accuracy of all other algorithms with a stunning 99.37%.
Facial micro-expression classification through an optimized convolutional neural network using genetic algorithm Santosh Naidana, Krishna; Yarra, Yaswanth; Prasanna Divvela, Lakshmi
Bulletin of Electrical Engineering and Informatics Vol 14, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i1.8048

Abstract

Computer vision facilitates machines to interpret the visual world using various computer aided detection (CAD)-based techniques. It plays a crucial role in micro-expression auto classification. A micro-expression is a brief facial movement which reveals a genuine emotion that a person tries to conceal, it usually lasts for a short duration and is imperceptible with normal vision. To reveal people’s genuine emotions, an automatic micro-expression screening using convolutional neural network (CNN) is in great need. Traditional methods for micro-expression recognition (MER) suffer from low classification accuracy due to inadequate CNN hyperparameters selection. The proposed approach addresses these challenges by using an optimized CNN with adequate learning rate, batch size, epochs, and dropout rate. Real-coded genetic algorithm (RCGA) has been employed for the hyperparameter optimization. In this experimentation, features are extracted from the onset and apex frames of microexpression video clips of CASME II dataset. The proposed model's performance is measured using various metrics, including accuracy, precision, and recall. The proposed approach’s performance is then compared with an optimized CNN using random search algorithm. The empirical investigation of existing CNN-based methods has proven efficacy of our proposed model.
Integration of genetic algorithm and mesoscopic modeling for the optimization of membrane separation processes Umarova, Zhanat; Makhanova, Zlikha; Zhumatayev, Nurlybek; Kopzhassarova, Asylzat; Suieuova, Nabat; Imanbayeva, Aigul; Yegenova, Aliya
Bulletin of Electrical Engineering and Informatics Vol 14, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i1.8268

Abstract

This article is dedicated to the development of an innovative approach to optimizing membrane separation processes. The paper introduces the integration of a genetic algorithm (GA) and mesoscopic modeling to enhance the efficiency and accuracy of process parameter optimization. The GA is employed for evolutionary search of optimal parameters, such as pressure, temperature, and membrane material characteristics. The use of evolutionary principles allows for efficient exploration of parameter space, identifying optimal solutions. Mesoscopic modeling serves as a tool for detailed analysis and visualization of membrane separation processes. It involves modeling the interaction of molecules with the membrane surface, enabling a more accurate consideration of the physicochemical aspects of the process. The integration of the GA and mesoscopic modeling creates a unique tool for membrane separation process optimization. The developed approach contributes not only to improving component separation efficiency but also to minimizing energy consumption. The method presented in the article has been successfully tested on model membrane process systems and demonstrated significant improvements compared to traditional optimization methods. The research results confirm the potential of the proposed approach for application in membrane technology industries, opening new perspectives in the field of separation process optimization.

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