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31,456 Article Results

Vision: a web service for face recognition using convolutional network

10.12928/telkomnika.v18i3.14790
Akino; Universitas Multimedia Nusantara Archilles , Arya; Universitas Multimedia Nusantara Wicaksana
This paper proposes a face recognition module built as a web service. We introduce a novel design and mechanism for face recognition on a web platform and to memorize most recent users for the user. This web service is called Vision and developed using the Flask and TensorFlow deep learning framework. The face recognition process is powered by FaceNet deep convolutional network model. The face recognition process done by Vision could also be utilized for user authentication and user memorization, both done in on a web platform. As a demonstration of concept and viability, in this study, Vision is integrated into a web-based voice chatbot. The testing and evaluation of Vision’s face recognition process show an overall F-score of one for all test scenarios.
Volume: 18
Issue: 3
Page: 1389-1396
Publish at: 2020-06-01

Vietnamese handwritten character recognition using convolutional neural network

10.11591/ijai.v9.i2.pp276-281
Truong Quang Vinh , Le Hoai Duy , Nguyen Thanh Nhan
Handwriting recognition is one of the core applications of computer vision for real-word problems and it has been gaining more interest because of the progression in this field. This paper presents an efficient model for Vietnamese handwriting character recognition by Convolutional Neural Networks (CNNs) – a kind of deep neural network model can achieve high performance on hard recognition tasks. The proposed architecture of the CNN network for Vietnamese handwriting character recognition consists of five hidden layers in which the first 3 layers are convolutional layers and the last 2 layers are fully-connected layers. Overfitting problem is also minimized by using dropout techniques with the reasonable drop rate. The experimental results show that our model achieves approximately 97% accuracy.
Volume: 9
Issue: 2
Page: 276-281
Publish at: 2020-06-01

Solar-powered flood early warning system with short message service (SMS) notifications

10.11591/ijeecs.v18.i3.pp1156-1162
Nur Anis Athirah , N. H. Radzi , M. N. Abdullah , S. A. Jumaat , N. Z. Mohamad
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. 
Volume: 18
Issue: 3
Page: 1156-1162
Publish at: 2020-06-01

Radiation beam scanning for leaky wave antenna by using slots

10.12928/telkomnika.v18i3.15720
Jamal S.; Universiti Teknikal Malaysia Melaka Kasim , M.S. M.; Universiti Teknikal Malaysia Melaka Isa , Z.; Universiti Teknikal Malaysia Melaka Zakaria , M. I.; United Arab Emirates University Hussein , Mowafak K.; University of Kerbala Mohsen
This paper provides an insight of a new, microstrip leaky wave antenna. It holds the ability to continue steer its beam at a swapping frequency. This is done with acceptable impedance matching while scanning and very little gain variation. Investigation is carried out on LWAs’ control radiation pattern in steps at a band frequency via vertical and horizontal slots. The enhancement is realized by etching horizontal and vertical slots on the radiation element. This study also presents a novel half-width microstrip leaky wave antenna (LWA). The antenna is made up of the following basic structures group’s vertical and horizontal slots. The reactance profile at the microstrip’s free edge and thus the main beam direction is changed once the control-cell states are changed. The radiation pattern direction changes by sweeping the operating frequency between 4 GHz to 6 GHz.The main beam may be directed by the antenna between 15o and 55o. C band achieved the measured peak gain of the antenna of 10 dBi at 4.3 GHz beam scanning range.
Volume: 18
Issue: 3
Page: 1237-1242
Publish at: 2020-06-01

A new model for large dataset dimensionality reduction based on teaching learning-based optimization and logistic regression

10.12928/telkomnika.v18i3.13764
Hind Raad; Al Salam University College Ibraheem , Zahraa Faiz; Al Salam University College Hussain , Sura Mazin; Mustansiriyah University Ali , Mohammad; Aliraqia University Aljanabi , Mostafa Abdulghafoor; University Polytechnic of Bucharest Mohammed , Tole; Universitas Ahmad Dahlan Sutikno
One of the human diseases with a high rate of mortality each year is breast cancer (BC). Among all the forms of cancer, BC is the commonest cause of death among women globally. Some of the effective ways of data classification are data mining and classification methods. These methods are particularly efficient in the medical field due to the presence of irrelevant and redundant attributes in medical datasets. Such redundant attributes are not needed to obtain an accurate estimation of disease diagnosis. Teaching learning-based optimization (TLBO) is a new metaheuristic that has been successfully applied to several intractable optimization problems in recent years. This paper presents the use of a multi-objective TLBO algorithm for the selection of feature subsets in automatic BC diagnosis. For the classification task in this work, the logistic regression (LR) method was deployed. From the results, the projected method produced better BC dataset classification accuracy (classified into malignant and benign). This result showed that the projected TLBO is an efficient features optimization technique for sustaining data-based decision-making systems.
Volume: 18
Issue: 3
Page: 1688-1694
Publish at: 2020-06-01

Simulation and modeling of two-level DC/DC boost converter using ARX, ARMAX, and OE model structures

10.11591/ijeecs.v18.i3.pp1172-1179
M.A.N. Amran , A.A. Bakar, , M.H.A. Jalil , M.U. Wahyu , A.F.H.A. Gani
This paper presents simulation and modeling of two-level DC/DC boost converter using system identification technique. The main objective is to identify the unknown mathematical model from designated converter that has 2 modes of operation. Signals from the converter were processed based on the impulse response from input and output voltages, which were in time domain data. Auto Regressive with eXogenous (ARX), Auto Regressive Moving Average with eXogenous (ARMAX), and Output-Error (OE) model structure techniques had been employed to generate a model from the converter, whose validation was based on coefficient of determination (R2) or best fits criterion. The result shows that the ARX model structure produced the best model with 94.03%, compared to ARMAX and OE with 93.70% and 92.25% respectively. In terms of stability for open-loop analysis, the ARX model structure gave the most stable system.
Volume: 18
Issue: 3
Page: 1172-1179
Publish at: 2020-06-01

Prediction schizophrenia using random forest

10.12928/telkomnika.v18i3.14837
Zuherman; Universitas Indonesia Rustam , Glori Stephani; Universitas Indonesia Saragih
Schizophrenia is a mental illness with a very bad impact on sufferers, attacking the part of human brain that disables the ability to think clearly. In 2018, Rustam and Rampisela classified Schizophrenia by using Northwestern University Schizophrenia Data, based on 66 variables consisting of group, demographic, and questionnaires statistics, based on the scale for the assessment of negative symptoms (SANS), and scale for the assessment of positive symptoms (SAS), and then classifiers that used are SVM with Gaussian kernel and Twin SVM with linear and Gaussian kernel. Furthermore, this research is novel based on the use of random forest as a classifier, in order to predict Schizophrenia. The result obtained is reported in percentage of accuracy, both in training and testing of random forest, which was 100%. This classification, therefore, shows the best value in contrast with prior methods, even though only 40% of training data set was used. This is very important, especially in the cases of rare disease, including schizophrenia.
Volume: 18
Issue: 3
Page: 1433-1438
Publish at: 2020-06-01

Variable speed control for 2Ph-HSM in RGS: a comparative simulation study

10.11591/ijece.v10i3.pp2285-2295
Salam Waley Shneen , Mohammed Qasim Sulttan , Manal Hadi Jaber
There are many applications of two-phase hybrid stepping motor (2Ph-HSM) system. The robotic grinding system (RGS) one of these applications. In this work, under the title variable speed control. The aim is Simulink the 2Ph-HSM in RGS with a proportional-integral controller (PIC) and optimization unit such as Genetic Algorithm (GA) which tuning PIC as (GA_PIC) to improve the RGS action by improving the parameters of PIC. Also comparing the act of PIC and GA_PIC to see which state is the best. The simulation results of this work show the GA_PIC is the best that comparative with PIC.
Volume: 10
Issue: 3
Page: 2285-2295
Publish at: 2020-06-01

On the performance of code word diversity based quasi orthogonal space time block codes in multiple-input-multiple-output systems

10.11591/ijece.v10i3.pp2535-2542
SenthilKumar Kumaraswamy , Palanivelan Manickavel , Noormohammed Valimohamad , Helanvidhya Thankaraj , Yogalakshmi Venkatesan , Bakyalakshmi Veeraragavan
In the recent past, a lot of researches have been put into designing a Multiple-Input-Multiple-Output (MIMO) system to provide multimedia services with higher quality and at higher data rate. On par with these requirements, a novel Quasi Orthogonal Space Time Block Code (QOSTBC) scheme based on code word diversity is proposed, which is a multi-dimensional approach, in this paper. The term code word diversity is coined, since the information symbols were spread across many code words in addition to traditional time and spatial spreading, without increasing transmission power and bandwidth. The receiver with perfect channel state information estimates the transmitted symbols with less probability of error, as more number of samples is available to estimate given number of symbols due to the extra diversity due to code words. The simulation results show a significant improvement in the Bit Error Rate (BER) performance of the proposed scheme when compared with the conventional schemes.
Volume: 10
Issue: 3
Page: 2535-2542
Publish at: 2020-06-01

Characterising and detection of botnet in P2P network for UDP protocol

10.11591/ijeecs.v18.i3.pp1584-1595
Noor Zuraidin Mohd Safar , Noryusliza Abdullah , Hazalila Kamaludin , Suhaimi Abd Ishak , Mohd Rizal Mohd Isa
Developments in computer networking have raised concerns of the associated Botnets threat to the Internet security. Botnet is an inter-connected computers or nodes that infected with malicious software and being controlled as a group without any permission of the computer’s owner. This paper explores how network traffic characterising can be used for identification of botnet at local networks. To analyse the characteristic, behaviour or pattern of the botnet in the network traffic, a proper network analysing tools is needed. Several network analysis tools available today are used for the analysis process of the network traffic. In the analysis phase, the botnet detection strategy based on the signature and DNS anomaly approach are selected to identify the behaviour and the characteristic of the botnet. In anomaly approach most of the behavioural and characteristic identification of the botnet is done by comparing between the normal and anomalous traffic. The main focus of the network analysis is studied on UDP protocol network traffic. Based on the analysis of the network traffic, the following anomalies are identified, anomalous DNS packet request, the NetBIOS attack, anomalous DNS MX query, DNS amplification attack and UDP flood attack. This study, identify significant Botnet characteristic in local network traffic for UDP network as additional approach for Botnet detection mechanism.
Volume: 18
Issue: 3
Page: 1584-1595
Publish at: 2020-06-01

POGIL model on mathematical connection ability viewed from self-regulated learning

10.11591/ijere.v9i2.20321
Enyta Ramadisae Putri , Budiyono Budiyono , Diari Indriati
One area of education which has not escaped efforts to improve the Indonesian government is mathematics education. The Indonesian government must make good use of mathematics learning so that students can use the mathematical mindset to offset the pace of global competition. This research is an experimental research on the Process-Oriented Guided Inquiry Learning (POGIL) model on the ability of mathematical connections in terms of self-regulated learning. The design used in this study was a 2 × 3 factorial. The research sample was 179 students from 7th grade in three State Junior High Schools in Sukoharjo Regency, Central Java, Indonesia. The research sample consisted of an experimental group that subjected to the POGIL model and a control group that subjected to a direct learning model. This research instrument used was a written test and questionnaire. The data analysis technique used was a two-way ANOVA test with unbalanced cells and post hoc test. The results showed that: 1) the POGIL model produces better mathematical connection ability than the direct learning model, 2) Students with high category self-regulated learning have better mathematical connection ability than medium and low categories, and students with self-regulated learning the medium category have better mathematical connection ability than the low category.
Volume: 9
Issue: 2
Page: 394-400
Publish at: 2020-06-01

Comparison between piezoelectric transformer and electromagnetic transformer used in electronic circuits

10.12928/telkomnika.v18i3.14334
Wedian Hadi Abd Al; Mustansiriyah University Ameer , Mustafa A. Fadel; Mustansiriyah University Al-Qaisi , Ammar; Mustansiriyah University Al-Gizi
This paper presents study, modeling and simulation of the piezoelectric material works as transformer (piezoelectric transformer (PT)) in power electronic circuits, comparisons are made with the regular transformer (iron core) works in the same circuit, the tested circuit is the full bridge converter which used in the simulation as dc power supply circuit. As a result, a detailed simulation for both the piezoelectric transformer and traditional transformer are achieved, as well as the output voltage from the dc power supply is tested by varying the load resistance. The dc power supply circuit has been simulated using PSIM (V9.1) power electronic circuit simulation software.
Volume: 18
Issue: 3
Page: 1567-1572
Publish at: 2020-06-01

STATCOM controllers based on fuzzy PI approach

10.11591/ijeecs.v18.i3.pp1138-1147
Tamer Shehata , Mohamed S Abdul moteleb , Essam Mohamed Abou El-Zahab
The electricity companies enforced some legislation on the electricity consumption contracts because the electricity network cannot bear the increasing demands of consumers. Therefore, a new controlling system is required to improve the frequent variations of the power system operating point (OP). Consequently, the flexible AC transmission systems (FACTS) controllers should be able to integrate with recent OP. Coordination of FACTS controller is more sophisticated due to various OP and uncertainties parametric in cooperation with the non linearity of power system (PS). Static Synchronous Compensator (STATCOM) plays very important role like the stability support of large and small transient-disturbance in PS. Therefore, the aim of this research is presents fuzzy logic (FL) with the PI controller (a novel controller) its ability to improve the performance of the power system along with the capability of switch irregular and rough actual world data. This new controlling system may be suitable for a wide range of applications especially the models which deal with huge and complicated data analysis. This new controller system carries out the adjustments of the voltage on DC capacitor under transient and steady-state conditions.
Volume: 18
Issue: 3
Page: 1138-1147
Publish at: 2020-06-01

Single camera depth control in micro class ROV

10.12928/telkomnika.v18i3.14885
Simon; Telkom University Siregar , Muhammad Ikhsan; Telkom University Sani , Sintong Tua Parlindungan; Telkom University Silalahi
Navigation is one of the main challenges in an underwater vehicle. To measure and sustain the depth in the micro class remotely operated vehicle (ROV) robot is one of the main demands in the underwater robot competition. There are many sensors that can be used to measure the depth; one of the sensors is using a single camera sensor. In this works, camera-based depth control is developed and evaluated for micro class ROV, namely as fitoplankton SAS ROV. Fitoplankton SAS ROV is a micro ROV prototype with six thrusters. To maintain the depth position, a PID control system with a camera-based depth sensor as the input of the setpoint is used. Moreover, the method for the camera to measure the distance is using the triangle similarity method. In this paper, the experimental scenario is using the rectangular marker to measure the distance, and the value of the depth is processing in the ground control station (GCS). The GCS will send the thruster value to control the depth, which depends on the PID control system. The experiment results show an average of depth accuracy of 95.74% to the depth setpoint.
Volume: 18
Issue: 3
Page: 1546-1552
Publish at: 2020-06-01

Parameter tuning of software effort estimation models using antlion optimization

10.12928/telkomnika.v19i3.16907
Marrwa Abd-AlKareem; University of Mosul Alabajee , Najla Akram; University of Mosul AlSaati , Taghreed Riyadh; University of Mosul Alreffaee
In this work, the antlion optimization (ALO) is employed due to its efficiency and wide applicability to estimate the parameters of four modified models of the basic constructive cost model (COCOMO) model. Three tests are carried out to show the effectiveness of ALO: first, it is used with Bailey and Basili dataset for the basic COCOMO Model and Sheta’s Model 1 and 2, and is compared with the firefly algorithm (FA), genetic algorithms (GA), and particle swarm optimization (PSO). Second, parameters of Sheta’s Model 1 and 2, Uysal’s Model 1 and 2 are optimized using Bailey and Basili dataset; results are compared with directed artificial bee colony algorithm (DABCA), GA, and simulated annealing (SA). Third, ALO is used with Basic COCOMO model and four large datasets, results are compared with hybrid bat inspired gravitational search algorithm (hBATGSA), improved BAT (IBAT), and BAT algorithms. Results of Test1 and Test2 show that ALO outperformed others, as for Test3, ALO is better than BAT and IBAT using MAE and the number of best estimations. ALO proofed achieving better results than hBATGSA for datasets 2 and 4 out of the four datasets explored in terms of MAE and the number of best estimates.
Volume: 19
Issue: 3
Page: 817-828
Publish at: 2020-06-01
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