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Website quality of Malaysian Technical University

10.11591/ijeecs.v18.i3.pp1624-1628
Lim Pui Jie , Rohaizan Ramlan , Rohayanti Hassan , Rashidah Omar , Chan Shau Wei
University website is the platform for university to interact with people. It is also an interphase for people to infer and getting known about the university. In addition, quality of the university website is vital to let people get positive response to the university. Therefore, university website should be evaluated for better performance. This study evaluate website of Malaysian Technical University (MTUN) on year of 2016 based on the criteria selected using online web diagnostics tools. There are nine criteria selected to measure the website; load time, response time, page rank, traffic, design optimization, page size, number of items, markup validation and broken link. The result shows website of UMP performed better in design optimization, page rank and markup validation. Meanwhile, UTHM performed in page rank, load time and page size. UTEM excellences in response time, number of items and broken link. Lastly, UniMAP performed in traffic criteria only. However, the (MTUN) University website is almost not meets with the criteria that selected with the quality standard that have been suggested. 
Volume: 18
Issue: 3
Page: 1624-1628
Publish at: 2020-06-01

Features detection based blind handover using kullback leibler distance for 5G HetNets systems

10.11591/ijai.v9.i2.pp193-202
Adnane El Hanjri , Aawatif Hayar , Abdelkrim Haqiq
The Fifth Generation of Mobile Networks (5G) is changing the cellular network infrastructure paradigm, and Small Cells are a key piece of this shift. But the high number of Small Cells and their low coverage involve more Handovers to provide continuous connectivity, and the selection, quickly and at low energy cost, of the appropriate one in the vicinity of thousands is also a key problem. In this paper, we propose a new method, to have an efficient, blind and rapid handover just by analysing Received Signal probability density function instead of demodulating and analysing Received Signal itself as in classical handover. The proposed method exploits KL Distance, Akaike Information Criterion (AIC) and Akaike weights, in order to decide blindly the best handover and the best Base Station (BS) for each user
Volume: 9
Issue: 2
Page: 193-202
Publish at: 2020-06-01

Improved quality of service-based cloud service ranking and recommendation model

10.12928/telkomnika.v18i3.11915
Sirisha; Koneru Lakshmaiah Education Foundation Potluri , Katta Subba; Koneru Lakshmaiah Education Foundation Rao
One of the ongoing technologies which are used by large number of companies and users is cloud computing environment. This computing technology has proved that it provides certainly a different level of efficiency, security, privacy, flexibility and availability to its users. Cloud computing delivers on demand services to the users by using various service-based models. All these models work on utility-based computing such that users pay for their used services. Along with the various advantages of the cloud computing environment, it has its own limitations and problems such as efficient resource identification or discovery, security, task scheduling, compliance and sustainability. Among these resource identification and scheduling plays an important role because users always submits their jobs and expects responses in least possible time. Research is happening all around the world to optimize the response time, make span so as to reduce the burden on the cloud resources. In this paper, QoS based service ranking model is proposed for cloud computing environment to find the essential top ranked services. Proposed model is implemented in two phases. In the first phase, similarity computation between the users and their services is considered. In the second phase, computing the missing values based on the computed similarity measures is calculated. The efficiency of the proposed ranking is measured and the average precision correlation of the proposed ranking measure is showing better results than the existing measures.
Volume: 18
Issue: 3
Page: 1252-1258
Publish at: 2020-06-01

Efficient and secure real-time mobile robots cooperation using visual servoing

10.11591/ijece.v10i3.pp3022-3034
Soumia Boudra , Nasr-Eddine Berrached , Amine Dahane
This paper deals with the challenging problem of navigation in formation of mobiles robots fleet. For that purpose, a secure approach is used based on visual servoing to control velocities (linear and angular) of the multiple robots. To construct our system, we develop the interaction matrix which combines the moments in the image with robots velocities and we estimate the depth between each robot and the targeted object. This is done without any communication between the robots which eliminate the problem of the influence of each robot errors on the whole. For a successful visual servoing, we propose a powerful mechanism to execute safely the robots navigation, exploiting a robot accident reporting system using raspberry Pi3. In addition, in case of problem, a robot accident detection reporting system testbed is used to send an accident notification, in the form of a specifical message. Experimental results are presented using nonholonomic mobiles robots with on-board real time cameras, to show the effectiveness of the proposed method.
Volume: 10
Issue: 3
Page: 3022-3034
Publish at: 2020-06-01

Deep hypersphere embedding for real-time face recognition

10.12928/telkomnika.v18i3.14787
Ryann; De La Salle University Alimuin , Elmer; De La Salle University Dadios , Jonathan; De La Salle University Dayao , Shearyl; De La Salle University Arenas
With the advancement of human-computer interaction capabilities of robots, computer vision surveillance systems involving security yields a large impact in the research industry by helping in digitalization of certain security processes. Recognizing a face in the computer vision involves identification and classification of which faces belongs to the same person by means of comparing face embedding vectors. In an organization that has a large and diverse labelled dataset on a large number of epoch, oftentimes, creates a training difficulties involving incompatibility in different versions of face embedding that leads to poor face recognition accuracy. In this paper, we will design and implement robotic vision security surveillance system incorporating hybrid combination of MTCNN for face detection, and FaceNet as the unified embedding for face recognition and clustering.
Volume: 18
Issue: 3
Page: 1671-1677
Publish at: 2020-06-01

Fault classification in smart distribution network using support vector machine

10.11591/ijeecs.v18.i3.pp1148-1155
Ong Wei Chuan , Nur Fadilah Ab Aziz , Zuhaila Mat Yasin , Nur Ashida Salim , Norfishah A. Wahab
Machine learning application have been widely used in various sector as part of reducing work load and creating an automated decision making tool. This has gain the interest of power industries and utilities to apply machine learning as part of the operation. Fault identification and classification based machine learning application in power industries have gain significant accreditation due to its great capability and performance. In this paper, a machine-learning algorithm known as Support Vector Machine (SVM) for fault type classification in distribution system has been developed. Eleven different types of faults are generated with respect to actual network. A wide range of simulation condition in terms of different fault impedance value as well as fault types are considered in training and testing data. Right setting parameters are important to learning results and generalization ability of SVM. Gaussian radial basis function (RBF) kernel function has been used for training of SVM to accomplish the most optimized classifier. Initial finding from simulation result indicates that the proposed method is quick in learning and shows good accuracy values on faults type classification in distribution system. The developed algorithm is tested on IEEE 34 bus and IEEE 123 bus test distribution system. 
Volume: 18
Issue: 3
Page: 1148-1155
Publish at: 2020-06-01

2D mapping using omni-directional mobile robot equipped with LiDAR

10.12928/telkomnika.v18i3.14872
Muhammad; Institut Teknologi Sepuluh Nopember Rivai , Dony; Institut Teknologi Sepuluh Nopember Hutabarat , Zishwa Muhammad Jauhar; Institut Teknologi Sepuluh Nopember Nafis
A room map in a robot environment is needed because it can facilitate localization, automatic navigation, and also object searching. In addition, when a room is difficult to reach, maps can provide information that is helpful to humans. In this study, an omni-directional mobile robot equipped with a LiDAR sensor has been developed for 2D mapping a room. The YDLiDAR X4 sensor is used as an indoor scanner. Raspberry Pi 3 B single board computer (SBC) is used to access LiDAR data and then send it to a computer wirelessly for processing into a map. This computer and SBC are integrated in robot operating system (ROS). The movement of the robot can use manual control or automatic navigation to explore the room. The Hector SLAM algorithm determines the position of the robot based on scan matching of the LiDAR data. The LiDAR data will be used to determine the obstacles encountered by the robot. These obstacles will be represented in occupancy grid mapping. The experimental results show that the robot is able to follow the wall using PID control. The robot can move automatically to construct maps of the actual room with an error rate of 4.59%.
Volume: 18
Issue: 3
Page: 1467-1474
Publish at: 2020-06-01

Chaos synchronization in a 6-D hyperchaotic system with self-excited attractor

10.12928/telkomnika.v18i3.13672
Ahmed S.; University of Mosul Al-Obeidi , Saad Fawzi; University of Mosul AL-Azzawi
This paper presented stability application for chaos synchronization using a 6-D hyperchaotic system of different controllers and two tools: Lyapunov stability theory and Linearization methods. Synchronization methods based on nonlinear control strategy is used. The selecting controller's methods have been modified by applying complete synchronization. The Linearization methods can achieve convergence according to the of complete synchronization. Numerical simulations are carried out by using MATLAB to validate the effectiveness of the analytical technique.
Volume: 18
Issue: 3
Page: 1483-1490
Publish at: 2020-06-01

Development of stereo matching algorithm based on sum of absolute RGB color differences and gradient Matching

10.11591/ijece.v10i3.pp2375-2382
Rostam Affendi Hamzah , M. G. Yeou Wei , N. Syahrim Nik Anwar
This paper proposes a new stereo matching algorithm which uses local-based method. The Sum of Absolute Differences (SAD) algorithm produces accurate result on the disparity map for the textured regions. However, this algorithm is sensitive to low texture areas and high noise on images with high different brightness and contrast. To get over these problems, the proposed algorithm utilizes SAD algorithm with RGB color channels differences and combination of gradient matching to improve the accuracy on the images with high brightness and contrast. Additionally, an edge-preserving filter is used at the second stage which is known as Bilateral Filter (BF). The BF filter is capable to work with the low texture areas and to reduce the noise and sharpen the images. Additionally, BF is strong  against the  distortions due to high brightness and contrast. The proposed work in this paper produces accurate results and performs much better compared with some established algorithms. This comparison is based on the standard quantitative measurements using the stereo benchmarking evaluation from the Middlebury.
Volume: 10
Issue: 3
Page: 2375-2382
Publish at: 2020-06-01

Communication between PLC different vendors using OPC server improved with application device

10.12928/telkomnika.v18i3.14757
Ignatius Deradjad; Politeknik Mekatronika Sanata Dharma Pranowo , Y. B. Theo; Politeknik Mekatronika Sanata Dharma Bagastama , Thomas A. F.; Politeknik Mekatronika Sanata Dharma Wibisono
Many industries often use different devices and controllers in automation systems. They all face the same difficulty how to exchange data between all those components. This paper proposed the implementation of OPC Server as software interface on communication between two different controllers, PLC Mitsubishi and PLC Omron. The main advantage of the method is the compatibility and solution for the factory difficulty problem because of using several driver controller. The compatibility among the different platforms of both controller, PLC Mitsubishi and PLC Omron, can be reached by use of KEPServerEx6 (OPC server) as a software interface. To test the compatibility amongst two different controllers, there was developed and implemented two field application devices, bottle unscramble and bottle filling station. This implementation shows OPC Server technology resolving data compatibility issues between different platforms and reducing development costs. It is envisaged that the method can be very useful to realize integration.
Volume: 18
Issue: 3
Page: 1491-1498
Publish at: 2020-06-01

Training configuration analysis of a convolutional neural network object tracker for night surveillance application

10.11591/ijai.v9.i2.pp282-289
Zulaikha Kadim , Mohd Asyraf Zulkifley , Nor Azwan Mohamed Kamari
Automated surveillance during the night is important as it is the period when crimes usually happened. By providing continuous monitoring, coupled with a real-time alert system, appropriate action can be taken immediately if a crime is detected. However, low lighting conditions during the night can degrade the quality of surveillance videos, where the captured images will have low contrast and less discriminative features. Consequently, these factors contribute to the problem of bad appearance representation of the object of interest in the tracking algorithm. Thus, a convolutional neural network-based object tracker for night surveillance is proposed by exploiting the deep feature strength in representing object features spatially and semantically. The proposed convolutional network consists of six layers that consist of three convolutional neural networks (CNN) and three fully connected (FC) layers. The network will be trained by using a binary classifier approach of objects and its background classes, which is updated on a fixed interval so that it fully encapsulates the changes in object appearance as it moves in the scene.  The algorithm has been tested with different sets of training data configurations to find the best optimum ones with regards to VOT2015 evaluation protocols, tested on 14-night surveillance videos. The results show that the configuration of a total of 250 training samples with a sample ratio of 4:1 between positive and negative data delivers the best performance for the sequence length of [1,550]. It can be inferred that more information on the object is required compared to the background, where the background might be homogeneous due to low lighting conditions. In conclusion, this algorithm is suitable to be implemented for night surveillance application.
Volume: 9
Issue: 2
Page: 282-289
Publish at: 2020-06-01

Novel dependencies of currents and voltages in power system steady state mode on regulable parameters of three-phase systems symmetrization

10.12928/telkomnika.v18i3.15113
Phu Tran; Industrial University of Ho Chi Minh City Tin , Duy-Hung; Ton Duc Thang University Ha , Minh; Ton Duc Thang University Tran , Quang Sy; Hong Bang International University Vu , Thanh-Tai; Ton Duc Thang University Phan
The unbalanced mode, negative/zero sequence, variation of real power are caused by the nonlinear or unbalanced loads increase the power transmission losses in distributing power systems and also harmful to the electric devices. Reactive power compensation is considered as the common methods for overcoming asymmetry. The critical issue in reactive power compensation is the optimal calculation of compensation values that is extremely difficult in complex circuits. We proposed a novel approach to overcome these difficulties by providing the creation of new analytical connections of the steady-state mode parameters (voltages, currents) depends on the controlled parameter for the arbitrary circuits. The base of our approach to reactive power compensation is the fractional-polynomial functions. We present a new description of the behavior of voltages and currents depending on the controlled parameters of the reactive power compensation devices, and we prove its effectiveness.
Volume: 18
Issue: 3
Page: 1195-1202
Publish at: 2020-06-01

Decomposition of color wavelet with higher order statistical texture and convolutional neural network features set based classification of colorectal polyps from video endoscopy

10.11591/ijece.v10i3.pp2986-2996
A. S. M. Shafi , Mohammad Motiur Rahman
Gastrointestinal cancer is one of the leading causes of death across the world. The gastrointestinal polyps are considered as the precursors of developing this malignant cancer. In order to condense the probability of cancer, early detection and removal of colorectal polyps can be cogitated. The most used diagnostic modality for colorectal polyps is video endoscopy. But the accuracy of diagnosis mostly depends on doctors' experience that is crucial to detect polyps in many cases. Computer-aided polyp detection is promising to reduce the miss detection rate of the polyp and thus improve the accuracy of diagnosis results. The proposed method first detects polyp and non-polyp then illustrates an automatic polyp classification technique from endoscopic video through color wavelet with higher-order statistical texture feature and Convolutional Neural Network (CNN). Gray Level Run Length Matrix (GLRLM) is used for higher-order statistical texture features of different directions (Ɵ = 0o, 45o, 90o, 135o). The features are fed into a linear support vector machine (SVM) to train the classifier. The experimental result demonstrates that the proposed approach is auspicious and operative with residual network architecture, which triumphs the best performance of accuracy, sensitivity, and specificity of 98.83%, 97.87%, and 99.13% respectively for classification of colorectal polyps on standard public endoscopic video databases.
Volume: 10
Issue: 3
Page: 2986-2996
Publish at: 2020-06-01

Simple broadband circularly polarized monopole antenna with two asymmetrically connected U-shaped parasitic strips and defective ground plane

10.12928/telkomnika.v18i3.14313
Hussein; University Teknikal Malaysia Melaka (UTeM) Alsariera , Z.; University Teknikal Malaysia Melaka (UTeM) Zakaria , A. A. M.; University Teknikal Malaysia Melaka (UTeM) Isa , Sameer; University Teknikal Malaysia Melaka (UTeM) Alani , M. Y.; University Teknikal Malaysia Melaka (UTeM) Zeain , Othman S.; University Teknikal Malaysia Melaka (UTeM) Al-Heety , S.; Multimedia Universty Ahmed , Mussa; University Teknikal Malaysia Melaka (UTeM) Mabrok , R.; University Teknikal Malaysia Melaka (UTeM) Alahnomi
A simple compact broadband circularly polarized monopole antenna, which comprises a simple monopole, a modified ground plane with an implementing triangular stub and two asymmetrically connected U-shaped parasitic strips, is proposed. Simulation results show that the proposed compact antenna (0.62λo×0.68λo) achieves a 10-dB impedance bandwidth (IBW) of 111% (1.7 to 5.95 GHz) and a 3-dB axial ratio bandwidth (ARBW) of 61% (3.3–6.2 GHz) with a peak gain between 2.9–4 dBi for the entire ARBW. With its broad IBW and ARBW, compact size and simple structure, the proposed antenna is suitable for different wireless communications.
Volume: 18
Issue: 3
Page: 1169-1175
Publish at: 2020-06-01

Predicting student performance in higher education using multi-regression models

10.12928/telkomnika.v18i3.14802
Leo Willyanto; Petra Christian University Santoso , Yulia; Petra Christian University Yulia
Supporting the goal of higher education to produce graduation who will be a professional leader is a crucial. Most of universities implement intelligent information system (IIS) to support in achieving their vision and mission. One of the features of IIS is student performance prediction. By implementing data mining model in IIS, this feature could precisely predict the student’ grade for their enrolled subjects. Moreover, it can recognize at-risk students and allow top educational management to take educative interventions in order to succeed academically. In this research, multi-regression model was proposed to build model for every student. In our model, learning management system (LMS) activity logs were computed. Based on the testing result on big students datasets, courses, and activities indicates that these models could improve the accuracy of prediction model by over 15%.
Volume: 18
Issue: 3
Page: 1354-1360
Publish at: 2020-06-01
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