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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 75 Documents
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Search results for , issue "Vol 13, No 6: December 2024" : 75 Documents clear
Enhanced multi-lingual Twitter sentiment analysis using hyperparameter tuning k-nearest neighbors Nugroho, Kristiawan; Winarno, Edy; Setiadi, De Rosal Ignatius Moses; Farooq, Omar
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.v13i6.7265

Abstract

Social media is a medium that is often used by someone to express themselves. These various problems on social media have encouraged research in sentiment analysis to become one of the most popular research fields. Various methods are used in sentiment analysis research, ranging from classic machine learning (ML) to deep learning. Researchers nowadays often use deep learning methods in sentiment analysis research because they have advantages in processing large amounts of data and providing high accuracy. However, deep learning also has limitations on the longer computational side due to the complexity of its network architecture. K-nearest neighbor (KNN) is a robust ML method but does not yet provide high-accuracy results in multi-lingual sentiment analysis research, so a hyperparameter tuning KNN approach is proposed. The results showed that using the proposed method, the accuracy level improved to 98.37%, and the classification error (CE) improved to 1.63%. The model performed better than other ML and even deep learning methods. The results of this study indicate that KNN using hyperparameter tuning is a method that contributes to the sentiment analysis classification model using the Twitter dataset.
Design of mapping system for domestic service robot using light detection and ranging Attamimi, Muhammad; Gunawan, Felix; Purwanto, Djoko; Dikairono, Rudy; Irfansyah, Astria Nur
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.v13i6.8007

Abstract

Service robots are becoming increasingly essential in offices or domestic environments, usually called domestic service robots (DSR). They must navigate and interact seamlessly with their surroundings, including humans and objects, which relies on effective mapping and localization. This study focuses on mapping, employing the light detection and ranging (LiDAR) sensor. The sensor, tested at proximity, gathers distance data to generate two-dimensional maps on a mini-PC. Additionally, it provides rotational positioning and robot odometry, broadening coverage through robot movement. A microcontroller with wireless smartphone connectivity facilitates control via Bluetooth. The robot is also equipped with ultrasonic sensors serving as a bumper. Testing in rooms of varying sizes using three methods (i.e., Hector simultaneous localization and mapping (SLAM), Google Cartographer, and real-time appearance-based mapping (RTAB-Map)) yielded good quality maps. The best F1-measure value was 96.88% achieved by Google Cartographer. All the results demonstrated the feasibility of this approach for DSR development across diverse applications.
Gaussian filter and CNN based framework for accurate detection of brain tumor by analyzing MRI images Sivakumar, S; Chaudhari, Poonam; Thatavarti, Satish; Sucharitha, G.; Mahesh, Basuthkar; Raghuvanshi, Abhishek
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.v13i6.6778

Abstract

The diagnosis of cancer can be challenging and time-consuming due to the complex characteristics of tumors and inherent noise in medical imaging. The significance of early detection and localization of tumors must be considered. Radiological imaging techniques can detect and potentially forecast the presence of neoplastic growths at various phases. The expeditiousness of the diagnosis process can be notably enhanced by amalgamating these images with algorithms designed for segmentation and relegation. Early detection of tumors and accurate localization of their position are critical factors. Medical scans, when used with segmentation and relegation procedures, enable the prompt and precise detection of cancerous tumor regions. The identification of malignant tumors enables this achievement. The present article introduces a framework for detecting brain tumors based on a convolutional neural network (CNN). The initial step in processing brain magnetic resonance imaging (MRI) images involves the application of a Gaussian filter to eliminate any noise present. Subsequently, CNN and long short-term memory (LSTM) deep learning methodologies are employed to classify images. CNN has demonstrated improved accuracy in the classification and detection of brain tumors. CNN has achieved an accuracy of 99.25% in cancer image classification. The sensitivity and specificity of CNN are also 98.75% and 99.25%, respectively.
Wideband coupled-line BPF with high-selectivity based on parallel transmission line signal interference technique for cellular base stations applications Firmli, Maroua; Zatni, Abdelkarim
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.v13i6.7782

Abstract

This paper presents a novel approach involving a modified wideband parallel coupled line bandpass filter (BPF). The proposed modification aims to achieve both enhanced skirt selectivity and simplified configuration, while ensuring the prevention from discontinuities between adjacent segments. The improvements in the performance of the filter’s structure are achieved through the integration of a signal-interference filtering model using parallel transmission line with distinct impedance values and electrical lengths at the input/output of the filter. This integration gives rise to the generation of multiple transmission zeros (TZs), thereby bolstering attenuation within both in-band and out-of-band frequency ranges. For the purpose of concept validation, a 3?? wideband band-pass filter with ?0=2.45 Ghz, accompanied by a fractional bandwidth of 50% was designed and simulated using microstrip RO6010 substrate. The outcomes of the simulation exhibit good performance, characterized by minimal insertion loss, wide bandwidth and the presence of seven TZs within the passband, resulting in high selectivity and sharp stopband rejection level.
Comparison of 5G performance post-merger between two network operators using field tests in urban areas Chatchalermpun, Surachai; Daengsi, Therdpong; Sriamorntrakul, Pakkasit; Phanrattanachai, Kritphon
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.v13i6.8307

Abstract

In late Q1/2023, DTAC and TRUE officially completed their merger. Consequently, this study was initiated to ascertain whether their respective fifth-generation (5G) networks had been seamlessly integrated several months following the merger. The investigation involved conducting drive tests along two predefined routes within the urban areas of Bangkok, employing the G-NetTrack pro tool for testing and data collection. Additionally, stationary tests were conducted in two crowded places using an application called Speedtest. Subsequently, an array of quality of service (QoS) metrics, including reference signal received power (RSRP), reference signal received quality (RSRQ), signal to noise ratio (SNR), download (DL), upload (UL) speeds and latency, were meticulously analyzed and presented. The findings of this study unveiled that, despite the successful completion of the DTAC and TRUE merger from a business standpoint, the technical integration of their respective 5G networks had not been finalized, although there were no significant differences between DTAC and TRUE for DL (p-value=0.542) and UL (p-value=0.090). Notably, significant differences were found between DTAC and TRUE for four metrics, including RSRP, RSRQ, SNR and latency (p-values0.05). Remarkably, roaming functionalities were still operational between the two networks.
Dynamics and kinematics of complex mechanical systems harnessing multibody dynamic program Kaidash, Mykhailo; Selevych, Serhii
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.v13i6.7721

Abstract

Understanding the behavior and performance of engineering applications like machines, transport machines, manipulators, and mechanisms like gears relies heavily on the study of the dynamics and kinematics of complex mechanical systems. This article provides a comprehensive overview of recent findings and advancements in this field. The purpose of this work is to provide an in-depth introduction to the theoretical and practical considerations involved in assessing the dynamic and kinematic properties of such complex systems. Understanding forces, torques, displacements, and velocities is highlighted as crucial to the design and study of complex mechanical systems, and the underlying mathematical models and concepts that control their motion are investigated. This paper also evaluates and critiques the most current developments in modeling and simulation approaches such as finite element analysis (FEA), computational dynamics, and optimization strategies. The multidisciplinary aspect of the topic and its potential to progress numerous engineering, robotics, and industrial applications constitute the topic's scientific uniqueness. The results include various advanced modeling and simulation techniques like FEA, computational dynamics, and multibody dynamics simulation. In conclusion, this article compiles a lot of information on the dynamics and kinematics of sophisticated mechanical systems, such as machines, transport machines, manipulators, and mechanisms.
A study on observing, detecting, and determining objects in low earth orbit using optical telescope system Le Xuan, Huy; Nguyen Tien, Su; Trinh Hoang, Quan; Le The, Soat; Trinh Van, Khang; Tran Anh, Tu; La Thuy, Linh
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.v13i6.8093

Abstract

Problems of space debris, space security threats and space accidents are an escalating topic that is drawing attention from scientists and researchers worldwide. Based on the practical demand for detecting and surveilling objects in Earth's orbit in the Vietnam's sky area, the research group has designed a space monitoring system to detect and identify orbiting objects using optical telescopes. The idea of this system is to utilize wide and narrow field-of-view (FOV) optical telescope systems to observe and identify the trajectory of orbiting objects. After an image of an unknown object is captured with a wide FOV telescope, an analyzing algorithm will process and predict the trajectory of it, with support of artificial intelligence, and determine whether there is the appearance of an uncataloged object. If it is affirmative, the narrow telescope system will adapt to a new attitude to track the object from predicted trajectory and gather information for future use. Constructing and validating of this monitoring system deployed by the research group are described in this paper.
A novel high-gain DC-DC converter for photovoltaic applications Thandavarayan, Porselvi; Mouttou, Arounassalame
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.v13i6.7862

Abstract

This manuscript proposes a novel transformer-less, single-switch direct current (DC)-DC converter for renewable energy systems (RESs). The main aim is to solve the problems of low output voltage generated by photovoltaic (PV) arrays and discontinuous input supply current caused by switching mode power supplies. The new converter is a combination of a single-ended primary inductor, a diode/capacitor circuit, and a conventional quadratic boost converter. The main advantages are the higher rate of voltage conversion (more than 10 times for duty cycle above 50%), the diminished voltage across the active switch with diodes, and diminished gate driver necessity because of the use of a single switch with a continual input current for raising the PV panel life. Furthermore, the new converter produces low switching voltage, which improves system efficiency. The proposed converter operating principle and analysis based on steady-state performance are discussed. The proposed converter’s performance is assessed using simulation in MATLAB/Simulink, and the results were presented. A 100 W prototype model of the designed DC-DC converter is also developed, and finally, the hardware results were compared with the simulated results.
Remote sensing in the analysis of the behavior of CO associated with confinement due to COVID-19, in the city of Manizales Henao-Céspedes, Vladimir; Garcés-Gómez, Yeison Alberto; Cardona-Morales, Oscar
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.v13i6.7441

Abstract

This article analyzed the behavior of carbon monoxide (CO) levels in Manizales during pre-lockdown, lockdown, and post-lockdown, as a response to the coronavirus disease (COVID-19) pandemic. The analysis focuses on the data of CO levels obtained from the tropospheric monitoring instrument (TROPOMI), precipitation, and temperature (T) recorded by the network of stations of Caldas. The data allowed us to find that during the lockdown, the average value of CO was 9.92% lower than the value registered before the lockdown, and it was 11.75% lower after the lockdown. On the other hand, the correlation between CO levels and population density during the three periods was analyzed, obtaining an ?2 = 0.816 after lockdown. Finally, considering other possible variables that can affect the CO levels, an analysis of the behavior of CO was carried out concerning the temperature and precipitation of the city registered before, during, and after the lockdown. Regarding CO and temperature, the correlation was inverse with Pearson’s ? = −0.599 (Fisher’s ? = −0.692), which also supports the decreasing trend of the value measured, and that the variation of CO levels does not depend only on lockdown but also on other factors. Regarding CO and precipitation, a positive correlation of Pearson’s ? = 0.165 (Fisher’s ? = 0.167) was obtained.
Design optimization and trajectory planning of a strawberry harvesting manipulator Saoud, Inas; Jaafari, Hatim Idriss; Chahboun, Asaad; Raissouni, Naoufal; Achhab, Nizar Ben; Azyat, Abdelilah
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.v13i6.7957

Abstract

This paper presents a systematic approach to optimizing the structural parameters of a 4-degree-of-freedom (DoF) strawberry harvesting manipulator to minimize its workspace. Unlike previous research that primarily concentrated on the spatial needs related to fruit distribution areas, this work addresses the spatial dynamics of different stages of the fruit-picking process. This is achieved by combining the workspace model method, mathematical modeling, and the GlobalSearch algorithm in the optimization process. A comprehensive verification was conducted using the Denavit-Hartenberg method to simulate the workspace of the optimal manipulator structure. This ensured that the manipulator effectively covered the entire harvesting space. The research design involves exploring an optimal trajectory planning method by adopting a modified sine jerk profile that minimizes overall trajectory duration while maintaining good smoothness. The effectiveness of this method is demonstrated through a simulation of the trajectory of the four joints to drive the end effector from the initial position to the position of the strawberry. This approach yields execution times up to 27% shorter than in previous studies. The proposed method is useful for optimizing the physical and trajectory design of the harvesting manipulator that operates in confined and restricted environments to enhance efficiency, adaptability, and safety in harvesting operations.

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