cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
-
Contact Email
-
Phone
-
Journal Mail Official
-
Editorial Address
-
Location
,
INDONESIA
Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
Published by IAES Indonesia Section and Partners
ISSN : 20893272     EISSN : -     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) is a peer reviewed International Journal in English published four issues per year (March, June, September and December). The aim of Indonesian Journal of Electrical Engineering and Informatics (IJEEI) is to publish high-quality articles dedicated to all aspects of the latest outstanding developments in the field of electrical engineering. Its scope encompasses the engineering of Telecommunication and Information Technology, Applied Computing & Computer, Instrumentation & Control, Electrical (Power), Electronics, and Informatics.
Arjuna Subject : -
Articles 783 Documents
 49   50   51   52   53 
Detection of Bundle Branch Blocks using Machine Learning Techniques Praveena S Kammath; Vrinda V Gopal; Jerry Kuriakose
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 3: September 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i3.3852

Abstract

The most effective method used for the diagnosis of heart diseases is the Electrocardiogram (ECG). The shape of the ECG signal and the time interval between its various components gives useful details about any underlying heart disease. Any dysfunction of the heart is called as cardiac arrhythmia. The electrical impulses of the heart are blocked due to the cardiac arrhythmia called Bundle Branch Block (BBB) which can be observed as an irregular ECG wave. The BBB beats can indicate serious heart disease. The precise and quick detection of cardiac arrhythmias from the ECG signal can save lives and can also reduce the diagnostics cost. This study presents a machine learning technique for the automatic detection of BBB. In this method both morphological and statistical features were calculated from the ECG signals available in the standard MIT BIH database to classify them as normal, Left Bundle Branch Block (LBBB) and Right Bundle Branch Block (RBBB). ECG records in the MIT- BIH arrhythmia database containing Normal sinus rhythm, RBBB, and LBBB were used in the study. The suitability of the features extracted was evaluated using three classifiers, support vector machine, k-nearest neighbours and linear discriminant analysis. The accuracy of the technique is highly promising for all the three classifiers with k-nearest neighbours giving the highest accuracy of 98.2%. Since the ECG waveforms of patients with the same cardiac disorder is similar in shape, the proposed method is subject independent. The proposed technique is thus a reliable and simple method involving less computational complexity for the automatic detection of bundle branch block. This system can reduce the effort of cardiologists thereby enabling them to concentrate more on treatment of the patients.
Swarm Intelligence Autotune For Differential Drive Wheeled Mobile Robot Muhammad Auzan; Roghib Muhammad Hujja; M Ridho Fuadin; Danang Lelono
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 3: September 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i3.3528

Abstract

Differential Drive Wheeled Mobile Robot (DDWMR) is a nonholonomic robot with constrained movement. Such constraint makes robot position control more difficult. A closed-loop control system such as PID can control robot position. However, DDWMR is a Multiple-Input-Multiple-Output system. There will be many feedback gains to be tuned, and the wrong value will make the system unstable. Therefore this research proposes an offline autotune method to choose optimal feedback gain that minimizes a fitness function. The fitness function uses Integral Absolute Error (IAE) and Integral Time Absolute Error (ITAE). These works propose to autotune feedback gain for DDWMR Jetbot, which implements a PI control system with six feedback gains. The methods used to tune the feedback gain are Particle Swarm Optimization (PSO) and Bird Swarm Algorithm (BSA). There are four different scenarios to do the autotune. The autotune result performance shows that those two methods can find an optimal gain to make the robot follow four different continuous trajectories without much trajectory deformation. PSO and BSA can do an autotune PI gain with six variables to minimize the Integral Absolute Error (IAE) and Integral Time Absolute Error (ITAE).
Spectral Efficiency Enhancement using Hybrid Pre-Coder Based Spectrum Handover Mechanism Annarao V Patil; Rohitha Ujjinimated
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 3: September 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i3.3690

Abstract

The use of Millimeter-wave (mm-Wave) has recently immensely enhanced in various communication applications due to massive technological developments in wireless communications. Furthermore, mm-Wave consists of a high bandwidth spectrum that can handle large demands of data transmission and internet services. However, high interference is observed in previous research at the time of spectrum handover from secondary (unlicensed) users to primary (licensed) users. Thus, interference reduction by achieving high spectral efficiency and an easy spectrum handoff process with minimum delay is an important research area. Therefore, a Hybrid Pre-coder Design based Spectrum Handoff (HPDSH) Algorithm is proposed in this article to increase spectrum efficiency in Cognitive Radio Networks(CRNs) and to access the large bandwidth spectrum of mm-Wave systems to meet the high data rate demands of current cellular networks. Moreover, a HPDSH Algorithm is presented to enhance spectral efficiency and this algorithm is utilized to take handover decisions and select backup channels. Here, different scenarios and parameters are considered to evaluate the performance efficiency of the proposed HPDSH Algorithm in terms of spectral efficiency and Signal to Noise (SNR) ratio. The proposed HPDSH Algorithm is compared against precoding methods like the OMP algorithm and SIC based methods.
Multi-objective Predictive Control of 3L-NPC Inverter Fed Sensorless PMSM Drives for Electrical Car Applications Paul Michael Dongmo Zemgue; Roland Christian Gamom Ngounou Ewo; Alexandre Teplaira Boum
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 3: September 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i3.3751

Abstract

This paper proposes a multi-objective FS-MPC approach based on three-step optimization for a surface-mounted PMSM fed by a 3L-NPC inverter. It helps to significantly reduce torque ripples, current harmonics while controlling the inverter's neutral point voltage. To overcome the drawbacks of using mechanical sensors, a sliding mode observer is used to estimate the machine speed and rotor angular position. Compared to existing works, the proposed control method is implemented using the proportionality between the electromagnetic torque and the current component on the q-axis to eliminate the computational redundancy related to the current and torque control. To further reduce torque ripples and current harmonics, a 3L-NPC inverter is used. Compared to other types of three-level inverters, it uses less power semiconductors and attenuates the problem of voltage fluctuation at the neutral point and current harmonics. Matlab/Simulink simulations of the proposed approach yield a current THD of 1.69 %.
Proposal of a Sizing Algorithm for an Optimal Design of DC/DC Converters Used in Photovoltaic Conversion Amrouayache Mohamed
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 3: September 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i3.3890

Abstract

The solar energy is converted to electrical energy by means of semiconductor materials called solar panels. However, the conversion efficiency is low, and hence the need to harvest the maximum power to optimize the photovoltaic conversion, for that the MPPT (Maximum Power Point Tracker) technique is used to maximize the power delivered by the solar panel (PV); this power is very fluctuating because it depends on the lightning and the temperature, the maximum power point is acquired by a DC / DC converter connected to the closed loop MPPT algorithm. The design of the circuit (the closed loop) must be robust in the face of changes in operating points caused by variations in meteorological conditions (temperature and lighting) and must always maintain certain performances such as stability, a fast and well-damped transient system, precision. In this paper, we presented a study of closed loop, for that, we established the average small signal model of the different topologies of the converters (boost; buck, buck-boost) to have a linear model. A comparative study between the three topologies has been established, to make an optimal choice of the circuit parameters.
Class-D Audio Amplifier using Sigma-Delta (ΣΔ) Modulator Nour El Imane Bellili; Khaled Bekhouche
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 3: September 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i3.3872

Abstract

Pulse width modulation and pulse density modulation are deemed to be main modulation techniques, even PDM could not emulate PWM, in terms of, basically, simplicity. PDM bitstream is encoded through sigma-delta modulation. Since sigma-delta modulation, compared to PWM, needs very high switching frequency and more complicated materials to compose circuits, it’s more difficult to design one. In this article we design a low-power class-D audio amplifier circuit where the analog signal is encoded into pulse density modulation (PDM) using a first-order sigma-delta (ΣΔ) modulator. The designed circuit is built using Orcad-PSpice and results are analyzed with Matlab. A second-order integrator, a voltage divider as a feedback loop are used to mitigate basically, THD and get high efficiency. The audio signal is passed to the EM speaker through a Butterworth low-pass filter. A low THD of less than 0.2 % is obtained comparing to similar circuits in the literature and a high efficiency of 92 % is achieved. 
QEEG as a Novel Parameter of Neuroplasticity in Elderly with Mild Cognitive Impairment Martina Wiwie Setiawan Nasrun; La Febry Andira Rose Cynthia; Nurhadi Ibrahim; Zenik Kusrini; Khamelia Malik; Wanarani Alwin
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 3: September 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i3.3555

Abstract

Neuroplasticity is the ability of the brain to change structurally and functionally in compensation for changes related to age or disease. In elderly people, the most common neuroplasticity problem is mild cognitive impairment (MCI). MCI is a syndrome defined as a decrease in cognitive function that is not appropriate for a person's age and educational level. One way to minimize the progress of deterioration in MCI is by doing physical exercise, such as walking. In this study, participants did physical activity by walking at least 4000 steps/day for 3 months. Cognitive function was measured by brain wave parameters with Quantitative Electroencephalography (QEEG). Electroencephalography (EEG) signals were recorded before and after the intervention. The EEG results showed that the QEEG wave parameters after the intervention increased in the alpha frequency band and decreased in the delta frequency band. 
ANFIS based Direct Torque Control of PMSM Motor for Speed and Torque Regulation Marulasiddappa Hallikeri Basappa; Pushparajesh Viswanathan
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 3: September 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/.v10i3.3775

Abstract

Nowadays, the Permanent Magnet Synchronous Motors (PMSM) are gaining popularity among electric motors due to their high efficiency, high-speed operation, ruggedness, and small size. PMSM motors comprise a trapezoidal electromotive force which is also called synchronous motors. Direct Torque Control (DTC) has been extensively applied in speed regulation systems due to its better dynamic behavior. The controller manages the amplitude of torque and stator flux directly using the direct axis current. To manage the motor speed, the torque error, flux error, and projected location of flux linkage are employed to adjust the inverter switching sequence via Space Vector Pulse Width Modulation (SVPWM). One of the most common problems encountered in a PMSM motor is Torque ripple, which is recreated by power electronic commutation and a better controller reduces the ripples to increase the drive's performance. Conventional controllers such as PI, PID and SVPWM-DTC were compared with the proposed Adaptive Neuro-Fuzzy Inference System (ANFIS) in terms of performance measures such as speed and torque ripple. In this work, the Two-Gaussian membership function of the ANFIS controller is used in conjunction with a PMSM motor to reduce torque ripple up to 0.53 Nm and maintain the speed with a distortion error of 2.33 %.
Development of Javanese Speech Emotion Database (Java-SED) Fatchul Arifin; Ardy Seto Priambodo; Aris Nasuha; Anggun Winursito; Teddy Surya Gunawan
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 3: September 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i3.3888

Abstract

Javanese is one of the most widely spoken regional languages in Indonesia, alongside other regional languages. Emotions can be recognized in a variety of ways, including facial expression, behavior, and speech. The recognition of emotions through speech is a straightforward process, but the outcomes are quite significant. Currently, there is no database for identifying emotions in Javanese speech. This paper aims to describe the creation of a Javanese emotional speech database. Actors from the Kamasetra UNY community who are accustomed to performing in dramatic roles participated in the recording. The location where recordings are made is free of interference and noise. The actors of Kamasetra have simulated six types of emotions, including happy, sad, fear, angry, neutral, and surprised. The cast consists of ten people between the ages of 20 and 30, including five men and five women. Both humans (30 Javanese-speaking verifiers ranging in age from 17 to 50) and a machine learning system (30 Javanese-speaking verifiers with ages between 17 and 50) verify the database that has been created. The verification results indicate that the database can be used for Javanese emotion recognition. The developed database is offered as open-source and is freely available to the research community at this link https://beais-uny.id/dataset/
FIR Filter Design using Raised Semi-ellipse Window Function Henry N. Uzo; Helen U. Nonyelu; Joy N. Eneh; ThankGod I. Ozue; Edward C. Anoliefo; Vincent C. Chijindu; Ogbonna U. Oparaku
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 3: September 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i3.3799

Abstract

In this paper, a new two-parameter window function - Raised semi-ellipse (RSE) is proposed. The window is obtained from a fixed elliptical window known as Semi-ellipse window by raising the radius of the minor axis by the parameter (β), and applied for the design of finite impulse response (FIR) digital filters. The spectral parameters of the proposed window are determined first and compared with the Kaiser window – a 2-parameter adjustable window. Subsequently, in its application in filter design with an established design algorithm, the newly proposed adjustable window is compared to the Semi-ellipse window to examine its improvement and also the Kaiser window to compare its performance with a commonly used adjustable window. The filter simulation results show that the filters designed with the proposed window can provide more reduced ripples than the Kaiser window for prescribed spectral characteristics.

Page 51 of 79 | Total Record : 783

 49   50   51   52   53 

Filter by Year

2013 2025


Reset
Filter By Issues
All Issue Vol 13, No 4: December 2025 Vol 13, No 3: September 2025 Vol 13, No 2: June 2025 Vol 13, No 1: March 2025 Vol 12, No 4: December 2024 Vol 12, No 3: September 2024 Vol 12, No 2: June 2024 Vol 12, No 1: March 2024 Vol 11, No 4: December 2023 Vol 11, No 3: September 2023 Vol 11, No 2: June 2023 Vol 11, No 1: March 2023 Vol 10, No 4: December 2022 Vol 10, No 3: September 2022 Vol 10, No 2: June 2022 Vol 10, No 1: March 2022 Vol 9, No 4: December 2021 Vol 9, No 3: September 2021 Vol 9, No 2: June 2021 Vol 9, No 1: March 2021 Vol 8, No 4: December 2020 Vol 8, No 3: September 2020 Vol 8, No 2: June 2020 Vol 8, No 1: March 2020 Vol 7, No 4: December 2019 Vol 7, No 3: September 2019 Vol 7, No 2: June 2019 Vol 7, No 1: March 2019 Vol 6, No 4: December 2018 Vol 6, No 3: September 2018 Vol 6, No 3: September 2018 Vol 6, No 2: June 2018 Vol 6, No 1: March 2018 Vol 5, No 4: December 2017 Vol 5, No 3: September 2017 Vol 5, No 2: June 2017 Vol 5, No 1: March 2017 Vol 4, No 4: December 2016 Vol 4, No 3: September 2016 Vol 4, No 2: June 2016 Vol 4, No 1: March 2016 Vol 3, No 4: December 2015 Vol 3, No 3: September 2015 Vol 3, No 2: June 2015 Vol 3, No 1: March 2015 Vol 2, No 4: December 2014 Vol 2, No 3: September 2014 Vol 2, No 3: September 2014 Vol 2, No 2: June 2014 Vol 2, No 1: March 2014 Vol 1, No 4: December 2013 Vol 1, No 3: September 2013 Vol 1, No 2: June 2013 Vol 1, No 1: March 2013 More Issue