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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
Arjuna Subject : -
Articles 65 Documents
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Search results for , issue "Vol 18, No 3: June 2020" : 65 Documents clear
A modified grey wolf optimizer for improving wind plant energy production Mohd Zaidi Mohd Tumari; Mohd Helmi Suid; Mohd Ashraf Ahmad
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1123-1129

Abstract

The main problem of existing wind plant nowadays is that the optimum controller of single turbine degrades the total energy production of wind farm when it is located in a large wind plant. This is owing to its greedy control policy that can not cope with turbulence effect between turbines. This paper proposes a Modified Grey Wolf Optimizer (M-GWO) to improvise the controller parameter of an array of turbines such that the total energy production of wind plant is increased. The modification employed to the original GWO is in terms of the updated mechanism. This modification is expected to improve the variation of exploration and exploitation rates while avoiding the premature convergence condition. The effectiveness of the M-GWO is applied to maximize energy production of a row of ten turbines. The model of the wind plant is derived based on the real Horns Rev wind plant in Denmark. The statistical performance analysis shows that the M-GWO provides the highest total energy production as compared to the standard GWO, Particle Swarm Optimization (PSO) and Safe Experimentation Dynamics (SED) methods.
An IoT based SMART patient health monitoring system C.R Srinivasan; Guru Charan; P Chenchu Sai Babu
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1657-1664

Abstract

Smart and connected health care is of specific significance in the spectrum of applications enabled the Internet of Things (IoT). Networked sensors, either embedded inside our living system or worn on the body, enable to gather rich information regarding our physical and mental health. In specific, the accessibility of information at previously unimagined scales and spatial longitudes combined with the new generation of smart processing algorithms can expedite an advancement in the medical field, from the current post-facto diagnosis and treatment of reactive framework, to an early-stage proactive paradigm for disease prognosis combined with prevention and cure as well as overall administration of well-being rather than ailment. This paper sheds some light on the current methods accessible in the Internet of Things (IoT) domain for healthcare applications. The proposed objective is to design and create a healthcare system centered on Mobile-IoT by collecting patient information from different sensors and alerting both the guardian and the doctor by sending emails and SMS in a timely manner. It remotely monitors the physiological parameters of the patient and diagnoses the illnesses swiftly. 
Design and development of three stages maximum power tracking solar charge controller N.H. Abdul Rahman; A. M. Omar; E. H. Mat Saat; N. I. Ilham; M. Z. Hussin; Yusrina Y
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1270-1278

Abstract

This paper presents the design of a Three Stages Maximum Power Point Tracking (MPPT) charge controller for improving the charging/discharging control of the battery. In this research, Buck Converter is used to regulate the voltage from the Photovoltaic (PV) module to the required voltage. This research is limited to Valve Regulated Lead Acid (VRLA) battery for 12V system voltage. The charge control algorithm envisages controlling the charging and discharging action in all the three stages of battery charging, bulk, absorption, and float. The idea is to control the battery charging and discharging status until meeting the battery set-point. The set-point is limited to High Voltage Disconnect (HVD), Low Voltage Disconnect (LVD) and Load Voltage Reconnect (LVR) to protect the battery from over-charging and deep-discharging. The results obtained demonstrate the good performance of the charge controller. With the application of the MPPT algorithm in the bulk stage, the time taken to get the battery to fully charged state becomes faster The regulation power from the converter to the inverter has performed well and the switching relay is managed to be controlled.
Solar-powered flood early warning system with short message service (SMS) notifications Nur Anis Athirah; N. H. Radzi; M. N. Abdullah; S. A. Jumaat; N. Z. Mohamad
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1156-1162

Abstract

Flood is one of the most common hazards in Malaysia. Flood effects can be local, or very large, affecting the neighborhood or community and entire river basins. This flood develops slowly; sometimes over a period of days while sometimes develop quickly in just few minutes. With the real time flood information, it will allow public safety organizations and other emergency managers to effectively plan their resource deployment within the limited time of alert. Hence, this project aims to design the solar powered flood alert warning system by using solar energy as the power supply. This system will send message using GSM to the residents to notify them about the flood occurred. In this project, three LEDs were used to indicate the height of the water levels which are safe, alert and danger conditions. Each of the height have different water level that indicates the level of safety for each condition. 
A simulation study of first-order autoregressive to evaluate the performance of measurement error based symmetry triangular fuzzy number Muhammad Shukri Che Lah; Nureize Arbaiy
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1559-1567

Abstract

Data collected by various data collection methods are often exposed to uncertainties that may affect the information presented by quantitative results. This also causes the forecasted model developed to be less precise because of the uncertainty contained in the input data used. Hence, preparing the data by means of handling inherent uncertainties is necessary to avoid the developed forecasting model to be less accurate. Traditional autoregressive (AR) model uses precise values and deals with the uncertainty normally in forecasting model. Fewer researches are focused on data preparation in time-series autoregressive for handling the uncertainties in data. Hence, this paper proposes a procedure to perform data preparation to handle uncertainty. The fuzzy data preparation involves the construction of fuzzy symmetric triangle numbers using percentage error and standard deviation method. The proposed approach is evaluated by using the simulation method for first-order autoregressive, AR (1) model in terms of forecasting accuracy performance. Simulation result demonstrates that the proposed approach obtains smaller error in forecasting and hence achieving better forecasting accuracy and dealing with uncertainty in the analysis.
Development of photodiode via the rapid melt growth (RMG) materials for energy conversion device Nurfarina Zainal; S. J.N. Mitchell; D. W. McNeill; W. M. Jubadi
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1188-1198

Abstract

Germanium (Ge) photodiodes were fabricated with the new RMG crucible materials that were established in this study. Results show that Ge large square patterns with size of 208 µm x 208 µm were unable to be achieved if ion implantation process was used in formation of photodiode. Delamination can be observed on all test samples during polycrystalline silicon (poly-Si) deposition at 620 oC. This result was in contrast to a previous intrinsic Ge test structure, where good formation of squares with size similar to that 208 µm x 208 µm had been successfully attained even with high annealing temperature above 938 oC. This indicates that doping through ion implantation has affected Ge film and caused delamination even at low temperature. However, good formations of Ge stripes were attained along with the ion implantation process in fabricating the photodiode. Results show that the sheet resistance of Ge stripe has significantly decreased compared to previous Ge resistors. The better resistance is due to the thicker (500 nm) Ge layer. In the case of Ge stripes with a p-i-n junction, only small fraction of test samples have shown a diode characteristic but with high leakage current. Results of I-V measurement show that a large fraction of test samples produced resistor characteristics. The high leakage current is believed due to the fact that the Ge films formed at this stage were polycrystalline in structure. Thus the grain size of Ge stripe has affected the performance. Slight changes on the I-V characteristic of single Ge can be observed when samples were tested under illumination. Therefore, it has potential to be used for future development of energy conversion device. 
Lung cancer transition rate by stages using discrete time markov model Muhammad Hakeem Omar; Syazreen Niza Shair; Nurin Haniah Asmuni
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1295-1302

Abstract

Morbidity risk is linked to the health status or a disease within a population. Morbidity risk is the risk of illness associated with health status or disease within a population. Cancer is one of the prime causes of both morbidity and mortality in majority of countries worldwide. In year 2016, the probability of Malaysian diagnosed with cancer before they reach age 75 is one over four. It has been reported that lung cancer has the highest deaths and it increased by 16.03% from 2012 to 2016. Malaysian National Cancer Registry reported that in year 2007 until 2011, 69.9% of lung cancer are men and the remaining 30.1% are women. Chinese become the dominant lung cancer cases representing 51.04% of total lung cancer patients in Malaysia followed by Malay, 44.81% and Indian, 4.16%. Treatments for lung cancer patients may vary by cancer stages. If cancer were just spread in one place, doctor may recommend a local treatment to get rid of cancer completely. Whereas, if a cancer has spread throughout the whole body, more comprehensive treatments may be needed. Therefore, knowing the probability of transition rate between cancer stages is important for healthcare cost effectiveness evaluation and expected cost calculation. This paper aims to estimate lung cancer transition rate by stages using the Functional Markov model. The Lung cancer transition rate will be calculated based on discrete time on a yearly basis. As a result, the probability of a Lung cancer patient recovering or deteriorating can be estimated.
Mobile edge computing for internet of things (IoT): security and privacy issues Atiqur Rahman; Guangfu Wu; Ali Md Liton
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1486-1493

Abstract

Nowadays, the masonry for environment-friendly and protected network structure designs, for example, the Internet of Things and gigantic data analytics are increasing at a faster pace compared to an earlier state. Mobile edge computing for an Internet of Things widget is information processing that is achieved at or close to the collectors of information in an Internet of Things system. Herein, we are proposing to temporarily evaluation the concepts, features, protection, and privacy applications of Internet of Things authorized mobile edge computing with its data protection view in our data-driven globe. We focus on illuminating one of kind components that need to be taken into consideration whilst creating a scalable, consistent, impenetrable and disseminated mobile edge computing structure. We also sum up the fundamental ideas regarding security threat alleviation strategies. After that, we walk around the existing challenges and opportunities in the area of mobile edge computing. In conclusion, we analyze a case study, in which a security protection mechanism can be hardened to lift out everyday jobs.
Implementation of persuasive design principles in mobile application development: a qualitative study Nor Afifah Shafin; RD Rohmat Saedudin; Nor Hazana Abdullah
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1464-1473

Abstract

Persuasive design principles (PDP) of persuasive system features framework have shown impressive results from the context of user engagement and acceptance as well as continuous usage towards the persuasive systems involved. Yet, available literatures do not thoroughly address the implementation of these design principles specifically in mobile applications and there is insufficient discussion on the impact of the principles in relation to the overall achievement of mobile applications. Hence, this research was conducted with the aim to qualitatively explore the way PDP were implemented across three different levels of mobile applications’ attainment. For this study, seven semi-structured interviews were conducted with the involvement of fifteen (15) Android mobile applications in the area of utilities category. These mobile applications were then categorized into three categories which is successful, partially successful and less successful based on their numbers of mobile applications downloaded for three consecutive years. The results from the content analysis revealed that each of the PDP were implemented in many ways yet the most common applied principles are reduction, tailoring and personalization. However, the analysis also shows low numbers of implementation from the system credibility and social support category. In addition, most of the mobile applications of the successful category have implemented a lot more PDP as compared to the other two mobile application categories. The results from this study has provide significance towards developers, practitioners as well as the scholars from the contextual perspective of persuasive system framework also the practical values of the principles specifically the implementation in mobile application development.
Deep learning in non coding variant (a brief overview) Lee Kuan Xin; Afnizanfaizal Abdullah
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1432-1438

Abstract

The 21st centuries were deemed to be the era of big data. Data driven research had become a necessity. This hold true not only in the business world, yet also in the field of biomedical world. From a few years of biological data extraction and derivation. With the advancement of Next Generation Sequencing, genomics data had grown to become an ambiguous giant which could not keep up with the pace of its advancement in it analysis counter parts. This results in a large amount of unanalysed genomic data. These genomic data consist not only plain information, researcher had discovered the potential of most gene called the non-coding variant and still failing in identifying their function. With the growth in volume of data, there is also a growth of hardware or technologies. With current technologies, we were able to implement a more complex and sophisticated algorithm in analysis these genomics data. The domain of deep learning had become a major interest of researcher as it was proven to have achieve a significant success in deriving insight from various field. This paper aims to review the current trend of non-coding variant analysis using deep learning approach.

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