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Artificial neural network and partial least square in predicting blood hemoglobin using near-infrared spectrum
Mohd Nazrul Effendy Mohd Idrus;
Kim Seng Chia
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 2: November 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v16.i2.pp701-708
Predictive models is crucial in near-infrared (NIR) spectroscopic analysis. Partial least square - artificial neural network (PLS-ANN) is a hybrid method that may improve the performance of prediction in NIR spectroscopic analysis. This study investigates the advantage of PLS-ANN over the well-known modelling in spectroscopy analysis that is partial least square (PLS) and artificial neural network (ANN). The results show that ANN that coupled with first order SG derivatives achieved the best prediction with root mean square error of prediction (RMSEP) of 0.3517 gd/L and coefficient of determination ( ) of 0.9849 followed by PLS-ANN with RMSEP of 0.4368 gd/L and of 0.9787, and PLS with RMSEP of 0.4669 gd/L and of 0.9727. This suggests that the spectrum information may unable to be totally represented by the first few latent variables of PLS and a nonlinear model is crucial to model these nonlinear information in NIR spectroscopic analysis.
A secure group based authentication protocol for machine to machine communications in LTE-WLAN interworking architecture
Mariya Ouaissa;
Abdallah Rhattoy
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 2: November 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v16.i2.pp848-859
Machine to Machine (M2M) communication has been used in applications such as telemetry, industry, automation and health. Support for a large number of devices has been considered an essential requirement in M2M communications. During this time, security is the most important challenge; M2M cannot access secure networks through effective authentication, all relevant M2M applications cannot be accepted. The challenge of M2M research is authentication by the group when a large number of M2M devices simultaneously accessing the network will cause severe authentication signaling congestion. The group based model under an M2M architecture, especially when the Machine Type Communication (MTC) devices belong to the non 3rd Generation Partnership Project (3GPP) network, will face a new challenge of access authentication. In this paper, we propose a group based authentication and key agreement protocol for machine type communications combining Elliptic Curve based Diffie-Hellman (ECDH) on the Extensible Authentication Protocol (EAP). Compared to EAP-AKA and other existing authentication protocols, our solution provides increased security against various malicious activities and better performance in terms of signaling overhead, bandwidth consumption and transmission cost.
Academician perceptions towards online student evaluation
Nor Hapiza Mohd Ariffin;
Siti Nor Hidayah Askol
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 2: November 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v16.i2.pp995-1001
In higher education institutions, student evaluation is important to ensure that students are given the opportunity to attain a high quality of education. In Universiti Teknologi Mara (UiTM) Malaysia, student evaluation was implemented through a system called Student Feedback Online (SuFO). This study aims to investigate and analyze the perception of academicians towards the usage of online student evaluation using SUFO in UiTM. The research employed the quantitative analysis and supported by Rasch measurement. The respondents are academicians in UiTM Shah Alam. A total of 152 academicians responded to the questionnaires. By using a Likert scale, 25 items were designed in the questionnaire and distributed by official email to the academicians. Data were analyzed using Rasch measurement to measure the validity and reliability of the items and the respondents involved in this research, while SPSS was used to analyze the quantitative data. The results showed that the academicians accepted the outcome value of student evaluation and they agreed that results of student evaluation should be used for formative assessment. It is recommended for future research, an instrument using a method of multi-dimensional evaluation of teaching should be developed to evaluate the effectiveness of university teaching.
Detecting candidates of depression, anxiety and stress through malay-written tweets: a preliminary study
Muhammad Zahier Nasrudin;
Ruhaila Maskat;
Ramli Musa
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 2: November 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v16.i2.pp787-793
Depression, anxiety and stress are not trivial conditions applicable for only the weak-hearted. They can be inflicted by anyone of all age groups, gender, race and social status. While some are courageous to acknowledge their condition, others shy away in shame or denial. In this paper, we proposed a “proactive” approach to detecting candidates of depression, anxiety and stress in an unobtrusive manner by tapping into what Malaysians tweet in Malay language. From this preliminary study, we constructed 165 Malay layman terms which describe depression, anxiety or stress as identified in M-DASS-42 scale. Since Twitter is an informal platform, construction of Malay layman terms is an essential step to the detection of candidates. Our study on 1,789 Malay tweets discovered 6 Twitter users as potential candidates, having high frequency of tweets with any of the layman terms. We can conclude that using tweets can be useful in unobtrusively detecting candidates of depression, anxiety or stress. This paper also identifies open research areas.
Hybrid MVDR-LMS beamforming for Massive MIMO
Yasmine M. Tabra;
Bayan Sabbar
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 2: November 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v16.i2.pp715-723
With the high speed of communication in LTE-5G, fast beamforming techniques need to be adopted. The training time required to form and steer the main lobes toward 5G multiple users must be short. Least-Mean-Square (LMS) training time is not suitable to work with in LTE-5G, but it has a good performance in forming multiple beams to large number of users and producing nulls in the interference direction. In this paper, an optimized hybrid MVDR-LMS beamforming algorithm is proposed to reduce the time required to estimate the antenna’s weights. This optimization is made by the benefit of previously set weights calculated using MVDR algorithms. The performance of the proposed hybrid MVDR-LMS algorithm tested using MATLAB 2016a.
Coordinated and optimal voltage control for voltage regulation using firefly algorithm
Muhamad Najib Kamarudin;
Tengku Juhana Tengku Hashim
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 2: November 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v16.i2.pp568-576
The operation and control of electricity in distribution networks has faced great challenges as a large number of distributed generations (DGs) are integrated. Connection of distributed generations (DGs) in the distribution system offers advantages in terms of reducing distribution and transmission costs as well as encouraging the use of renewable energy sources. The power flow in the distribution systems is no longer moving in a single direction and this resulted the system to become as active distribution networks (ADN). One of the main problems in ADN is the voltage regulation issue which is to maintain the voltage to be within its permissible limits. Several methods of voltage control methods are available and focus is given in finding the optimal voltage control using artificial intelligence techniques. This paper presents an optimal and coordinated voltage control method while minimizing losses and voltage deviation of the network. The optimal and coordinated voltage control scheme is implemented on an IEEE 13 bus distribution network for loss and voltage deviation minimization in the networks. Firefly Algorithm (FA) which is a known heuristic optimization technique for finding the optimal solution is used in this work. The results are compared with another optimization method known as Backtracking Search Algorithm (BSA) for identifying the best setting for solving the voltage regulation problem. In order to solve the multi-objective optimization issue, the MATPOWER load flow simulation is integrated in the MATLAB environment with the optimization algorithm.
Improved newton-raphson with schur complement methods for load flow analysis
Lea Tien Tay;
William Ong Chew Fen;
Lilik Jamilatul Awalin
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 2: November 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v16.i2.pp699-605
The determination of power and voltage in the power load flow for the purpose of design and operation of the power system is very crucial in the assessment of actual or predicted generation and load conditions. The load flow studies are of the utmost importance and the analysis has been carried out by computer programming to obtain accurate results within a very short period through a simple and convenient way. In this paper, Newton-Raphson method which is the most common, widely-used and reliable algorithm of load flow analysis is further revised and modified to improve the speed and the simplicity of the algorithm. There are 4 Newton-Raphson algorithms carried out, namely Newton-Raphson, Newton-Raphson constant Jacobian, Newton-Raphson Schur Complement and Newton-Raphson Schur Complement constant Jacobian. All the methods are implemented on IEEE 14-, 30-, 57- and 118-bus system for comparative analysis using MATLAB programming. The simulation results are then compared for assessment using measurement parameter of computation time and convergence rate. Newton-Raphson Schur Complement constant Jacobian requires the shortest computational time.
Heuristic based model for groceries shopping navigator
Muhammad Wardi bin Peeyee;
Shuzlina Abdul-Rahman;
Nurzeatul Hamimah Abdul Hamid;
Mohd Zaki Zakaria
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 2: November 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v16.i2.pp932-940
This paper presents a heuristic based model for groceries shopping navigator that attempts to improve the navigation problem that usually face by customers while doing their shopping. A system known as Shopping Navigator or shortly SHoNa was developed to give the optimal sequence of shelves to be visited by the customer and the total estimated shopping time so that the user can plan their shopping task earlier. Genetic algorithm was employed and implemented in a web-based platform that is compatible with other devices such as smartphones and tablets. SHoNA can minimize the shopping time by identifying the most optimal order of shelves inside the supermarket that needs to be visited by the customer. A series of experimental was performed in producing the optimum model. Our findings showed that the combination of order one crossover and inverse mutation produced a better optimal performance, which is the minimum total amount of groceries shopping time. SHoNA can be further enhanced with visualization features for a better shopping experience.
Two-chambers soft actuator bending and rotational properties for underwater application
Muhammad Rusydi Muhammad Razif;
Ahmad Athif Faudzi;
Ili Najaa Aimi Mohd Nordin;
Tariq Rehman;
Dyah Ekashanti Octorina Dewi
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 2: November 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v16.i2.pp669-677
This paper presents a study on bending and rotational properties of two-chambers soft actuator for underwater application. Previous study demonstrated the actuator characteristics required to optimize the bending performance and its potential to perform underwater because of the actuator material. However, there is less study of the actuator performance underwater as well as how the actuator tips rotating during actuator bending motion. In this paper, three tests have been proposed which are comparisons of bending angle simulation and experiment in air environment, bending angle performance in air and underwater environment as well as rotational angle of actuator tip in air environment. The bending angle of soft actuator is measured based on displacement in horizontal and vertical axis and for rotational angle, gyro sensor has been used. Based on the analysis, it is proven that the fabricated soft actuator performs almost similar trend to the simulation. It is also demonstrated that the actuator performs almost double bending motion underwater environment compared to in air environment at the same pressure, and the actuator is able to rotate 90º in air environment with the supplied pressure 52 kPa.
Automatic classification of paddy leaf disease
Shafaf Ibrahim;
Nurnazihah Wahab;
Ahmad Firdaus Ahmad Fadzil;
Nur Nabilah Abu Mangshor;
Zaaba Ahmad
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 2: November 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v16.i2.pp767-774
RiceisastaplefoodinmostoftheAsiancountries.Itisanimportantcrop, andoverhalfoftheworldpopulationreliesonitforfood.However,paddy leafdiseasecanaffectboththequalityandquantityofpaddyinagriculture production.Theclassificationofpaddyleafdiseaseisanimportantand urgenttaskasitdestroysabout10%to15%ofproductioninAsia.Thus,a studyonautomaticclassificationofpaddyleafdiseaseusingimage processingispresented.Featureextractiontechniquesofcolor,texture,and shapewereimplementedtoanalyzethecharacteristicsofthepaddyleaf disease.Inanother note,aSupportVector Machine(SVM)isused toclassify thefourtypesofpaddyleafdiseasewhicharethebrownspot,bacterialleaf blight,tungrovirus,andleaf scald.Theperformanceofthe proposedstudyis evaluatedto160testingimageswhichreturned86.25%ofclassification accuracy.Theoutcomeofthisstudyisexpectedtoassisttheagrotechnology industryinearlydetectionofpaddyleafdiseaseinwhichanappropriate actioncould be taken accordingly.