Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
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.
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<![CDATA[QEEG as a Novel Parameter of Neuroplasticity in Elderly with Mild Cognitive Impairment ]]>
<![CDATA[Martina Wiwie Setiawan Nasrun]]>;
<![CDATA[La Febry Andira Rose Cynthia]]>;
<![CDATA[Nurhadi Ibrahim]]>;
<![CDATA[Zenik Kusrini]]>;
<![CDATA[Khamelia Malik]]>;
<![CDATA[Wanarani Alwin]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 3: September 2022 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v10i3.3555
<![CDATA[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. ]]>
<![CDATA[ANFIS based Direct Torque Control of PMSM Motor for Speed and Torque Regulation ]]>
<![CDATA[Marulasiddappa Hallikeri Basappa]]>;
<![CDATA[Pushparajesh Viswanathan]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 3: September 2022 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/.v10i3.3775
<![CDATA[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 %.]]>
<![CDATA[Development of Javanese Speech Emotion Database (Java-SED) ]]>
<![CDATA[Fatchul Arifin]]>;
<![CDATA[Ardy Seto Priambodo]]>;
<![CDATA[Aris Nasuha]]>;
<![CDATA[Anggun Winursito]]>;
<![CDATA[Teddy Surya Gunawan]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 3: September 2022 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v10i3.3888
<![CDATA[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/]]>
<![CDATA[FIR Filter Design using Raised Semi-ellipse Window Function ]]>
<![CDATA[Henry N. Uzo]]>;
<![CDATA[Helen U. Nonyelu]]>;
<![CDATA[Joy N. Eneh]]>;
<![CDATA[ThankGod I. Ozue]]>;
<![CDATA[Edward C. Anoliefo]]>;
<![CDATA[Vincent C. Chijindu]]>;
<![CDATA[Ogbonna U. Oparaku]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 3: September 2022 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v10i3.3799
<![CDATA[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.]]>
<![CDATA[A Robust Controller Design for Simple Robotic Human Arm ]]>
<![CDATA[Wajdi Sadik Aboud]]>;
<![CDATA[Hadeel K. Aljobouri]]>;
<![CDATA[Hayder Sabah Abd Al-Amir]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 3: September 2022 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v10i3.3895
<![CDATA[Nowadays, the manipulator of two degrees of freedom (2DOF) has many applications. One is a human arm that may be utilized in robotic rehabilitation. The 2DOF controlled robot manipulator usually acts like human arms. This paper aims to design a robust, stable controller for the upper limb robotic model. A sliding mode control (SMC) approach is proposed to realize stability, tracing accuracy, and robustness for 2DOF robotic manipulator. Based on the general manipulator equation of motion, two SMCs are designed. The first is designed according to the input–output stability constraints. The second is designed according to the adaptive law. Not only the trajectory tracking is guaranteed but also stability is ensured. The stability of the controllers is examined based on Lyapunov stability criteria. The controllers and the robotic arm are formulated analytically. The MATLAB platform is adopted to examine and validate the proposed controller’s performance. The addition of adaptation law in the SMC scheme improves the results for the two designed controllers and shows remarkable trajectory tracking and system stability as well. The improvement rate shows an enhancement of 40.5% and 36.7% for manipulator joints 1 and 2, respectively.]]>
<![CDATA[On the Audio-Visual Emotion Recognition using Convolutional Neural Networks and Extreme Learning Machine ]]>
<![CDATA[Arselan Ashraf]]>;
<![CDATA[Teddy Surya Gunawan]]>;
<![CDATA[Fatchul Arifin]]>;
<![CDATA[Mira Kartiwi]]>;
<![CDATA[Ali Sophian]]>;
<![CDATA[Mohamed Hadi Habaebi]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 3: September 2022 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v10i3.3879
<![CDATA[The advances in artificial intelligence and machine learning concerning emotion recognition have been enormous and in previously inconceivable ways. Inspired by the promising evolution in human-computer interaction, this paper is based on developing a multimodal emotion recognition system. This research encompasses two modalities as input, namely speech and video. In the proposed model, the input video samples are subjected to image pre-processing and image frames are obtained. The signal is pre-processed and transformed into the frequency domain for the audio input. The aim is to obtain Mel-spectrogram, which is processed further as images. Convolutional neural networks are used for training and feature extraction for both audio and video with different configurations. The fusion of outputs from two CNNs is done using two extreme learning machines. For classification, the proposed system incorporates a support vector machine. The model is evaluated using three databases, namely eNTERFACE, RML, and SAVEE. For the eNTERFACE dataset, the accuracy obtained without and with augmentation was 87.2% and 94.91%, respectively. The RML dataset yielded an accuracy of 98.5%, and for the SAVEE dataset, the accuracy reached 97.77%. Results achieved from this research are an illustration of the fruitful exploration and effectiveness of the proposed system.]]>
<![CDATA[Characteristic Control of SWCNT-FET by Varying Its Chirality and Dimensions ]]>
<![CDATA[Zahraa Eisa]]>;
<![CDATA[Haider Al-Mumen]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 3: September 2022 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v10i3.4046
<![CDATA[Carbon nanotube (CNT) has witnessed great importance due to its electronic and mechanical properties. The CNTFET was designed to provide high-performance electronic devices. Therefore, the carbon nanotube is representing a potential material for future microelectronic devices. In this paper, COMSOL Multiphysics was used to design and a simulate single-walled carbon nanotube field-effect transistor with a back gate. The insulation layer used in the model was silicon dioxide. The influence of changing its thickness on the drain current was discussed. In addition, the specification of carbon nanotubes was investigated in terms of changing their diameter and length. Moreover, this paper reveals the current transport of CNTFET for different applied gate voltage and drain voltage. In our work, the CNTFET behaves as n-type FET with transconductance gm≈1.25uA and electron mobility equal to 4.77×10-26cm2v-1s-1. To obtain semiconducting properties for the CNT material, it must consider the chirality when altering the carbon nanotubes diameter. In the proposed device, the diameter values range from 1nm to 4.5nm. It was found that increasing the diameter range resulted in decreasing bandgap from 0.497 eV to 0.110 eV and increasing drain current from 4.075 uA to 31.33 uA.]]>
<![CDATA[Hinders of Cloud Computing Usage in Higher Education in Iraq: A Model Development ]]>
<![CDATA[Hayder Salah Hashim]]>;
<![CDATA[Ali Salah Alasady]]>;
<![CDATA[Zainab Amin Al-Sulam]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 3: September 2022 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v10i3.3908
<![CDATA[Cloud computing (CC) is a trendy technology that is being used in business and daily life. However, limited studies is found on higher education usage. The barriers and obstacles that confront the usage is not clear and in particular in developing countries. The purpose of this study is to examine the barriers and obstacle that confront the usage CC services in Barash University in Iraq. Using the technology organization environment framework and the internal external factor (IE-TOE), the study proposed the conceptual framework. The data was collected from academic, non-academic staff and students using convivence sampling technique. The data was analyzed using Smart PLS. The findings showed that organizational obstacle followed by technological, internal and external factors, and environmental factors are the most severe obstacles that confront the university in using CC services. Decision makers can benefit from the developed model to ease the implementation of CC.]]>
<![CDATA[Improvement of Multiple Antenna Sensing Technique for Detecting the White Space in a Spectrum Sharing System ]]>
<![CDATA[Zachaeus Kayode Adeyemo]]>;
<![CDATA[Samson Iyanda Ojo]]>;
<![CDATA[Saheed Abiona Abolude]]>;
<![CDATA[Damilare Oluwole Akande]]>;
<![CDATA[Hammed O. Lasisi]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 3: September 2022 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v10i3.3802
<![CDATA[Exact detection of White Space (WS) is one of the actions in a Spectrum Sharing System (SSS) to determine unused spectrum for proper utilization. However, exact detection of WS is being affected by channel impairments, resulting in harmful interference. The Existing Multiple Antenna Spectrum Sensing (EMASS) technique used in addressing this effect is characterized with noise uncertainty leading to low detection rate due to setting of thresholds that is based on noise variance. Hence, this paper proposes an Improved Multiple Antenna Spectrum Sensing (IMASS) for detecting the WS in a SSS. Various copies of licensed user’s signals are received through the unlicensed user antennas over different antenna configuration. The received signals are combined using a modified equal gain combiner and energy of the combined signal is determined using Parseval’s relation for a discrete time signal. The received signal is used to form a square matrix which is converted to covariance matrix. Characteristic equation is obtained from covariance matrix to determine the minimum eigenvalue. The ratio of energy to minimum eigenvalue of the received signal is obtained and used as test statistics. The IMASS technique is evaluated using Probability of Detection (PD) and Total Error Probability (TEP) by comparing with EMASS. The proposed IMASS technique gives better performance with higher PD and lower TEP values than EMASS at all different antenna configurations.]]>
<![CDATA[Dynamic Security Assessment For Power System Using Attribute Selection Technique ]]>
<![CDATA[Mohannad Abdulkhaliq Alhubaity]]>;
<![CDATA[Saraa Ismaeel Khalel]]>;
<![CDATA[Mohammed Ali Al-Rawe]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 3: September 2022 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v10i3.3928
<![CDATA[The evaluation of the dynamic security of the electrical power system after the occurrence of disturbances in the network is one of the most important tools that the control center uses to maintain the system in a safe operating mode, as well as prevent cases of system out of control and cases of complete shutdown. With the annual increase in the size of the electrical system and its distribution over a very wide geographical area, this led to a new challenge to assess dynamic security assessment (DSA), which is dealing with a huge and varied amount of data that requires processing in a very short time. To address these challenges, this study presented a new technique of artificial intelligence, which is the attribute selection technique, to reduce the size of this data and thus improve the accuracy and speed of results. This method relied on the combination of decision tree algorithms and a technique (Attribute selection) in the data obtained from the test system (IEEE-30Bus). The results of this method showed a significant reduction in the number of data used, which amounted to (45.55%) of the total data, Which led to an improvement in the classification accuracy, as the classification accuracy reached (97.27%). This reduction is very important when dealing in the online operating environment, as it saves the time necessary to reach the most accurate evaluation decision and thus issue gives a greater opportunity to take the appropriate decision in the event of disturbances and keep the electrical system in a secure state.]]>
