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[Structural adaptive anisotropic recursive filter for blind medical image deconvolution ]]>
<![CDATA[Tanawat Kwanpak]]>;
<![CDATA[Paramate Horkaew]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 7, No 2: June 2019 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v7i2.869
<![CDATA[Performance of radiographic diagnosis and therapeutic intervention heavily depends on the quality of acquired images. Over decades, a range of pre-processing for image enhancement has been explored. Among the most recent proposals is iterative blinded image deconvolution, which aims to identify the inheritant point spread function, degrading images during acquisition. Thus far, the technique has been known for its poor convergence and stability and was recently superseded by non-negativity and support constraints recursive image filtering. However, the latter requires a priori on intrinsic properties of imaging sensor, e.g., distribution, noise floor and field of view. Most importantly, since homogeneity assumption was implied by deconvolution, recovered degrading function was global, disregarding fidelity of underlying objects. This paper proposes a modified recursive filtering with similar non-negativity constraints, but also taking into account local anisotropic structure of content. The experiment reported herein demonstrates its superior convergence property, while also preserving crucial image feature.]]>
<![CDATA[Feature and muscle selection for an effective hand motion classifier based on electromyography ]]>
<![CDATA[Triwiyanto Triwiyanto]]>;
<![CDATA[Triana Rahmawati]]>;
<![CDATA[I Putu Alit Pawana]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 7, No 2: June 2019 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v7i2.867
<![CDATA[An issue that arises in the hand motion classification based on the electromyography (EMG) system is the failure of choosing the right features and number of muscles. These parameters are fundamental in determining the accuracy and effectiveness of the classifier system. Therefore, the objective of this study is to develop and evaluate an effective hand motion classifier based on the EMG signal. The three-channel of EMG was collected by placing three pairs of electrodes on the surface of the skin. Six statistic features (mean, variance, standard deviation, kurtosis, skewness, and entropy) were selected to extract the EMG signal using a window length of 100 samples. A muscle and features selection is applied to the classifier machine (linear discriminant analysis (LDA), support vector machine (SVM) and K nearest neighborhood (KNN)) to retrieve the most useful feature and muscle. In this study, we found that there was no significant difference in accuracy among a number of muscles (p-value>0.05). LDA and SVM showed the best accuracy and no significant difference in accuracy between both were found. This study concluded that EMG signal from a single muscle can classify the hand motion (hand close, open, wrist flexion, and extension) effectively. ]]>
<![CDATA[A modified genetic algorithm with a new crossover mating scheme ]]>
<![CDATA[Allemar Jhone P. Delima]]>;
<![CDATA[Ariel M. Sison]]>;
<![CDATA[Ruji P. Medina]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 7, No 2: June 2019 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v7i2.1047
<![CDATA[This study introduced the Inversed Bi-segmented Average Crossover (IBAX), a novel crossover operator that enhanced the offspring generation of the genetic algorithm (GA) for variable minimization and numerical optimization problems. An attempt to come up with a new mating scheme in generating new offspring under the crossover function through the novel IBAX operator has paved the way to a more efficient and optimized solution for variable minimization particularly on premature convergence problem using GA. A total of 597 records of student-respondents in the evaluation of the faculty instructional performance, represented by 30 variables, from the four State Universities and Colleges (SUC) in Caraga Region, Philippines were used as the dataset. The simulation results showed that the proposed modification on the Average Crossover (AX) of the genetic algorithm outperformed the genetic algorithm with the original AX operator. The GA with IBAX operator combined with rank-based selection function has removed 20 or 66.66% of the variables while 13 or 43.33% of the variables were removed when GA with AX operator and roulette wheel selection function was used.]]>
<![CDATA[Computation of current-resistance photovoltaic model using reverse triangular number for photovoltaic emulator application ]]>
<![CDATA[Razman Ayop]]>;
<![CDATA[Chee Wei Tan]]>;
<![CDATA[Kwan Yiew Lau]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 7, No 2: June 2019 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v7i2.1148
<![CDATA[PV emulator (PVE) is a power supply that produces similar current‑voltage (I‑V) characteristic as the PV module. It simplifies the testing of the PV system during the development phase. Since the output voltage and current of the PVE change based on various factors (load, irradiance and temperature), the computation of the operating point for the PVE is crucial. The resistance feedback control strategy is a robust and fast approach to find the operating point for the PVE. Nonetheless, it uses an uncommon current‑resistance PV model, which cannot be computed using the conventional approach. This work introduces the reverse triangular number to compute the PV model and obtained the operating point of the PVE. The reverse triangular number is based on the variable step sizes that allow fast computation of the PV model. The operating point is then used by the PI controller and the buck converter to produce the output voltage and current similar to the PV module. The results show that the reverse triangular number is able to compute the PV model accurately. In addition, the proposed PVE not only works well with resistive load but adapts accurately under the integration with maximum power point tracking converter.]]>
<![CDATA[Sliding mode control for altitude and attitude stabilization of quadrotor UAV with external disturbance ]]>
<![CDATA[A Noordin]]>;
<![CDATA[M A M Basri]]>;
<![CDATA[Z Mohamed]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 7, No 2: June 2019 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v7i2.1149
<![CDATA[This paper addresses the problem of robust altitude and attitude control of ‘×’ mode configuration quadrotor UAV using Lyapunov stability based sliding mode control with saturation function. The dynamic model of the quadrotor was derived by considering nonlinearity factor. MATLAB Simulink was used to simulate the model in two different conditions; without and with the presence of external disturbance. This was done to test the robustness of the control method. Simulation results showed that the sliding mode controller provides good performance and robustness against disturbance.]]>
<![CDATA[3D printed horn antenna using direct metal laser melting technique for millimetre wave applications ]]>
<![CDATA[Muataz W. Sabri]]>;
<![CDATA[M. K. A. Rahim]]>;
<![CDATA[F. Zubir]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 7, No 2: June 2019 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v7i2.1167
<![CDATA[A 3D printed horn antenna at ka-band is presented in this paper. The horn antenna is well known for high gain performance. The performance of the horn antenna manufactured using 3D printed technology is investigated in this work. The horn is designed based on WR-28 waveguide standard. The proposed horn is simulated by computer simulation technology (CST) software and fabricated using 3D printing direct metal laser melting technique. The 3D printing technique gives the antenna an advantage of being not just rapid manufactured but also low-cost and lightweight. However, several works reported on 3D printed devices highlight the effects of surface roughness and dimensional tolerance on the performances. Therefore, the printed horn is profiled to correlate the surface roughness and dimension tolerance towards the performance. The printed horn is measured using standard VNA. The results showed that the measured performance agreed fairly with the simulation with directive radiation pattern at 15 dBi gain. The printed horn has a weight of less than 130g and considerably working at Ka band regardless of the surface roughness resulted from the fabrication process.]]>
<![CDATA[Reliability of graphene as charge storage layer in floating gate flash memory ]]>
<![CDATA[M. Hilman Ahmad]]>;
<![CDATA[N Ezaila Alias]]>;
<![CDATA[Afiq Hamzah]]>;
<![CDATA[Zaharah Johari]]>;
<![CDATA[M. S. Z. Abidin]]>;
<![CDATA[Norlina Paraman]]>;
<![CDATA[M. L. Peng Tan]]>;
<![CDATA[Razali Ismail]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 7, No 2: June 2019 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v7i2.1170
<![CDATA[This study aims to investigate the memory performances of graphene as a charge storage layer in the floating gate with difference doping concentration of n-channel and p-channel substrates using Silvaco ATLAS TCAD Tools. The simulation work has been done to determine the performance of flash memory in terms of memory window, P/E characteristics and data retention and have been validated with the experimental work done by other researchers. From the simulation data, the trend of memory window at low P/E voltage is nearly overlapped between simulation and experimental data. The memory window at ±20V P/E voltage for n-channel and p-channel flash memory cell are 15.4V and 15.6V respectively. The data retention for the n-channel flash memory cell is retained by 75% (from 15.4V to 11.6V) whereas for the p-channel flash memory cell is retained by 80% (from 15.6V to 12.5V) after 10 years of extrapolation with -1/1V gate stress which shows that p-channel flash memory cell demonstrates better data retention compared to n-channel flash memory cell.]]>
<![CDATA[Modeling and simulation of a wirelessly-powered thermopneumatic micropump for drug delivery applications ]]>
<![CDATA[Marwan Nafea]]>;
<![CDATA[Jeevananthan Baliah]]>;
<![CDATA[Mohamed Sultan Mohamed Ali]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 7, No 2: June 2019 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v7i2.1175
<![CDATA[This paper presents modeling and finite element analysis of a thermopneumatic micropump with a novel design that does not affect the temperature of the working fluid. The micropump is operated by activating a passive wireless heater using wireless power transfer when the magnetic field is tuned to match the resonant frequency of the heater. The heater is responsible for heating an air-heating chamber that is connected to a loading reservoir through a microdiffuser element. The solution inside the reservoir is pumped through a microchannel that ends with an outlet hole. The thermal and pumping performances of the micropump are analyzed using finite element method over a low range of Reynold’s number ⩽ 10 that is suitable for various biomedical applications. The results demonstrate promising performance with a maximum flow rate of ∼2.86 μL/min at a chamber temperature of 42.5 ºC, and a maximum pumping pressure of 406.5 Pa. The results show that the developed device can be potentially implemented in various biomedical areas, such as implantable drug delivery applications.]]>
<![CDATA[Design and performance analysis of a twin T-bridge RC harmonic oscillation generator with an operational amplifier ]]>
<![CDATA[Boyan Karapenev]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 7, No 2: June 2019 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v7i2.694
<![CDATA[This paper presents the special features of harmonic generators and their widespread use and in particular the design, simulation and experimental studies of a twin T-bridge RC generator with an operational amplifier. The results obtained are analyzed and compared. For the particular implementation, the frequency error varies from 4 % in experimental studies to 6.7 % in the simulation, and in this case an average value of 5.35 % can be assumed.]]>
<![CDATA[Improved time quantum length estimation for round robin scheduling algorithm using neural network ]]>
<![CDATA[Sonia Zouaoui]]>;
<![CDATA[Lotfi Boussaid]]>;
<![CDATA[Abdellatif Mtibaa]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 7, No 2: June 2019 ]]>
Publisher : <![CDATA[IAES Indonesian Section ]]>
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DOI: 10.52549/ijeei.v7i2.464
<![CDATA[In most cases, the quantum time length is taken to be fix in all applications that use Round Robin (RR) scheduling algorithm. Many attempts aim to determination of the optimal length of the quantum that results in a small average turnaround time, but the unknown nature of the tasks in the ready queue make the problem more complicated: Considering a large quantum length makes the RR algorithm behave like a First Come First Served (FIFO) scheduling algorithm, and a small quantum length cause high number of contexts switching. In this paper we propose a RR scheduling algorithm based on Neural Network Models for predicting the optimal quantum length which lead to a minimum average turnaround time. The quantum length depends on tasks burst times available in the ready queue. Rather than conventional traditional methods using fixed quantum length, this one giving better results by minimizing the average turnaround time for almost any set of jobs in the ready queue.]]>
