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31,128 Article Results

Assessment Analytic Theoretical Framework Based on Learners’ Continuous Learning Improvement

10.11591/ijeecs.v11.i2.pp682-687
M. Hamiz , M. Bakri , Norhaslinda Kamaruddin , Azlinah Mohamed
Currently, university students are required to follow stringent curriculum structure regardless of their performance. Personalized learning is not being offered resulting the whole cohort must compy to a customized fixed curriculum design. This is because the designed curriculum does not take into account different students’ attainment. Furthermore, there is a mismatched between supply and demand of graduates’ skill sets to fulfil the requirement of industry. Due to these issues, employers face difficulties in finding suitable high-skilled worker which contributes to large number of unemployed graduates. Thus, a systematic intervention of students’ learning process is essential to construct informed and strategic responses in order to manage challenges and minimize skill mismatch, at the same time providing adequate fundamental knowledge. In this paper, an assessment analytics framework is proposed based on automated extracted skill sets from curriculum documents and individual performance to recommend adaptive learners’ learning system (ALLS). By preparing the graduates with the required industry skill sets, the graduates’ unemployment rate is envisaged to reduce.
Volume: 11
Issue: 2
Page: 682-687
Publish at: 2018-08-01

Metamodel-based Optimization of a PID Controller Parameters for a Coupled-tank System

10.12928/telkomnika.v16i4.9069
Marwan; Universiti Teknologi Malaysia Nafea , Abdul Rasyid Mohammad; Universiti Teknologi Malaysia Ali , Jeevananthan; Jabil Circuit Guangzhou Economic and Technological Development District Baliah , Mohamed Sultan; Universiti Teknologi Malaysia Mohamed Ali
Liquid flow and level control are essential requirements in various industries, such as paper manufacturing, petrochemical industries, waste management, and others. Controlling the liquids flow and levels in such industries is challenging due to the existence of nonlinearity and modeling uncertainties of the plants. This paper presents a method to control the liquid level in a second tank of a coupled-tank plant through variable manipulation of a water pump in the first tank. The optimum controller parameters of this plant are calculated using radial basis function neural network metamodel. A time-varying nonlinear dynamic model is developed and the corresponding linearized perturbation models are derived from the nonlinear model. The performance of the developed optimized controller using metamodeling is compared with the original large space design. In addition, linearized perturbation models are derived from the nonlinear dynamic model with time-varying parameters.
Volume: 16
Issue: 4
Page: 1590-1596
Publish at: 2018-08-01

An Early Drowning Detection System for Internet of Things (IoT) Applications

10.12928/telkomnika.v16i4.9046
Muhammad Ramdhan; Universiti Teknologi Malaysia MS , Muhammad; Universiti Teknologi Malaysia Ali , Paulson Eberechukwu; Universiti Teknologi Malaysia N , Nurzal Effiyana; Universiti Teknologi Malaysia G , Samura; Universiti Teknologi Malaysia Ali , Kamaludin; Universiti Teknologi Malaysia M.Y
Drowning is the leading cause of injury or death for children and teenagers. Designing a drowning detection device by implementing an Internet of Thing (IoT) is needed. An Early Drowning Detection System (EDDS) is a system that gives an early alarm to the guardians (parents and lifeguard) if the detector triggered an abnormal heartbeat and the victims are submerged under the water for a long time. A microcontroller was used to control the signal received from a pulse sensor and time for the signal lost under the water before it is transmitted to the access point. The access point acts as a data forwarding to the database via an internet connection. Universal Asynchronous Receiver/Transmitter (UART) 433MHz radio frequency transceiver has been used to create the wireless communication between drowning detection device and monitoring hub. A triggered warning signal will be transmitted to the guardians via Android apps and web page.
Volume: 16
Issue: 4
Page: 1870-1876
Publish at: 2018-08-01

Analysis of Quantization Noise and Power Estimation of Continuous-Time Delta Sigma Analog-to-Digital Converter Using Test Enable Feature For 4G Radios

10.11591/ijict.v7i2.pp82-88
Anil Kumar Sahu , Vivek Kumar Chandra , G R Sinha
This paper presents a novel approach for completely test enable feature and low-voltage delta– sigma analog-to-digital (A/D) converters for cutting edge wireless applications. Oversampling feature of ADCs and DACs is enough to meet the requirement related to in-band and adjacent channel leakage ratio (ACLR) execution of 3G/4G portable radio. The quantization noise which is not filtered in ADC is addressed. We have achieved work power-optimization and test enable feature of oversampling ADC is uses in design and simulation so that the problem of quantization error in continues time sigma delta ADC is solved. This paper suggests support to designer for selecting appropriate topologies with various channel arrangements, number of bits and oversampling issues. A test enable feature of CT A/D is presented introducing the test signal generation (TSG) and the COrdinate Rotation Digital Computer (CORDIC) for evaluating the performance of ADC. This helps in addressing the challenge of 4G and upcoming 5G wireless radio. System level plan of a delta–sigma modulator ADC for 4G radios is studied.
Volume: 7
Issue: 2
Page: 82-88
Publish at: 2018-08-01

Biometric Analysis of Leaf Venation Density Based on Digital Image

10.12928/telkomnika.v16i4.7322
Agus; Universitas Teknokrat Indonesia Ambarwari , Yeni; Bogor Agricultural University Herdiyeni , Irman; Bogor Agricultural University Hermadi
The density level in the leaf venation type has different characteristics. These different characteristics explain the environment in which plants grow, such as habitat, vegetation, physiology and climate. This research aims to measure of leaf venation density, leaf venation feature analysis and then identifying plants based on venation type. Stages of this research include leaf image data collection, segmentation, vein detection, feature extraction, feature selection, classification, evaluation and ending with analysis. The results of this study indicate that the level of leaf venation density is quite good is the type of venation paralellodromous, acrodromous and pinnate. Based on the selection of features using Boruta Algorithm, obtained 19 most important features that represent the type of leaf venation. This is reinforced by the average of accuracy produced at the time of classification using SVM, which amounted to 77.57%.
Volume: 16
Issue: 4
Page: 1735-1744
Publish at: 2018-08-01

Multi-class K-support Vector Nearest Neighbor for Mango Leaf Classification

10.12928/telkomnika.v16i4.8482
Eko; University of Bhayangkara Surabaya Prasetyo , R. Dimas; University of Bhayangkara Surabaya Adityo , Nanik; Institut Teknologi Sepuluh Nopember Suciati , Chastine; Institut Teknologi Sepuluh Nopember Fatichah
K-Support Vector Nearest Neighbor (K-SVNN) is one of methods for training data reduction that works only for binary class. This method uses Left Value (LV) and Right Value (RV) to calculate Significant Degree (SD) property. This research aims to modify the K-SVNN for multi-class training data reduction problem by using entropy for calculating SD property. Entropy can measure the impurity of data class distribution, so the selection of the SD can be conducted based on the high entropy. In order to measure performance of the modified K-SVNN in mango leaf classification, experiment is conducted by using multi-class Support Vector Machine (SVM) method on training data with and without reduction. The experiment is performed on 300 mango leaf images, each image represented by 260 features consisting of 256 Weighted Rotation- and Scale-invariant Local Binary Pattern features with average weights (WRSI-LBP-avg) texture features, 2 color features, and 2 shape features. The experiment results show that the highest accuracy for data with and without reduction are 71.33% and 71.00% respectively. It is concluded that K-SVNN can be used to reduce data in multi-class classification problem while preserve the accuracy. In addition, performance of the modified K-SVNN is also compared with two other methods of multi-class data reduction, i.e. Condensed Nearest Neighbor Rule (CNN) and Template Reduction KNN (TRKNN). The performance comparison shows that the modified K-SVNN achieves better accuracy.
Volume: 16
Issue: 4
Page: 1826-1837
Publish at: 2018-08-01

News Reliability Evaluation using Latent Semantic Analysis

10.12928/telkomnika.v16i4.9062
Guo; Multimedia University Xiaoning , Tan De; Multimedia University Zhern , Soo Wooi; Multimedia University King , Tan Yi; Multimedia University Fei , Lam Hai; Multimedia University Shuan
The rapid rise and widespread of ‘Fake News’ has severe implications in the society today. Much efforts have been directed towards the development of methods to verify news reliability on the Internet in recent years. In this paper, an automated news reliability evaluation system was proposed. The system utilizes term several Natural Language Processing (NLP) techniques such as Term Frequency-Inverse Document Frequency (TF-IDF), Phrase Detection and Cosine Similarity in tandem with Latent Semantic Analysis (LSA). A collection of 9203 labelled articles from both reliable and unreliable sources were collected. This dataset was then applied random test-train split to create the training dataset and testing dataset. The final results obtained shows 81.87% for precision and 86.95% for recall with the accuracy being 73.33%.
Volume: 16
Issue: 4
Page: 1704-1711
Publish at: 2018-08-01

K-Means Clustering and Genetic Algorithm to Solve Vehicle Routing Problem with Time Windows Problem

10.11591/ijeecs.v11.i2.pp462-468
Adyan Nur Alfiyatin , Wayan Firdaus Mahmudy , Yusuf Priyo Anggodo
Distribution is an important aspect of industrial activity to serve customers on time with minimal operational cost. Therefore, it is necessary to design a quick and accurate distribution route. One of them can be design travel distribution route using the k-means method and genetic algorithms. This research will combine k-means method and genetic algorithm to solve VRPTW problem. K-means can do clustering properly and genetic algorithms can optimize the route. The proposed genetic algorithm employs initialize chromosome from the result of k-means and using replacement method of selection. Based on the comparison between genetic algorithm and hybrid k-means genetic algorithm proves that k-means genetic algorithm is a suitable combination method with relative low computation time, are the comparison between 2700 and 3900 seconds.
Volume: 11
Issue: 2
Page: 462-468
Publish at: 2018-08-01

Fuzzy Logic Enhanced Direct Torque Control with Space Vector Modulation

10.11591/ijeecs.v11.i2.pp704-710
Siaw-Paw Koh , Sieh-Kiong Tiong , Kharudin Ali , Ahmed Abdalla
Over the past few years, multiple types of modifications have been proposed onto the Direct Torque Control (DTC) scheme. Among others is the implementation of Space Vector Modulation (SVM). In this paper, two new control strategies are proposed onto an SVM-DTC. Instead of using PI torque and flux controllers, a fuzzy logic control method is implemented in the proposed modification to achieve a more constant switching frequency while minimizing the torque error. The fuzzy logic controller controls the voltages in direct and quadratic reference frame (Vd, Vq). This approach fully utilizes the switching capability of the inverter and thus improving the overall system performance. To overcome issues in open loop stator flux such as DC drift and saturation, a closed loop estimation method of stator flux is also proposed based on voltage model and low pass filter. The performance of the proposed control strategy is benchmarked with that of a conventional DTC–SVM. Simulations and experiments were carried out and the results show that the proposed method outperforms the conventional DTC-SVM in terms of DC-offset elimination and overall system robustness. Over the past few years, multiple types of modifications have been proposed onto the Direct Torque Control (DTC) scheme. Among others is the implementation of Space Vector Modulation (SVM). In this paper, two new control strategies are proposed onto an SVM-DTC. Instead of using PI torque and flux controllers, a fuzzy logic control method is implemented in the proposed modification to achieve a more constant switching frequency while minimizing the torque error. The fuzzy logic controller controls the voltages in direct and quadratic reference frame (Vd, Vq). This approach fully utilizes the switching capability of the inverter and thus improving the overall system performance. To overcome issues in open loop stator flux such as DC drift and saturation, a closed loop estimation method of stator flux is also proposed based on voltage model and low pass filter. The performance of the proposed control strategy is benchmarked with that of a conventional DTC–SVM. Simulations and experiments were carried out and the results show that the proposed method outperforms the conventional DTC-SVM in terms of DC-offset elimination and overall system robustness. 
Volume: 11
Issue: 2
Page: 704-710
Publish at: 2018-08-01

Mixed Integer Linear Programming for Maintenance Scheduling in Power System Planning

10.11591/ijeecs.v11.i2.pp607-613
S.M. Hussin , M.Y. Hassan , L. Wu , M.P. Abdullah , N. Rosmin , M.A. Ahmad
This paper discussed the merit of mixed-integer linear programming (MILP)-based approach against Lagrangian relaxation (LR)-based approach in solving generation and transmission maintenance scheduling problem. MILP provides a straightforward solution by formulating coupling constraints equations so that these sub-problems can be solved simultaneously without involving multipliers. In LR-based approach, generation and transmission maintenance scheduling, and security-constrained unit commitment have been solved individually and the integration was realized through a series of multipliers which has caused computational burden to the system. Numerical case studies were evaluated on the 6-bus system. A comparative study is carried out between the MILP and LR approaches. Simulation results indicate that the maintenance schedule derived by the proposed MILP approach outperforms the LR in terms of operational cost savings and gap tolerance. The operating cost could be saved up to 5% and the gap tolerance achieved is 0.01% as compared to 0.14% by LR.
Volume: 11
Issue: 2
Page: 607-613
Publish at: 2018-08-01

Token-based Single Sign-on with JWT as Information System Dashboard for Government

10.12928/telkomnika.v16i4.8388
I Putu Arie; Udayana University Pratama , Linawati; Udayana University Linawati , Nyoman Putra; Udayana University Sastra
Various web-based information systems are developed by Indonesian government to improve quality of services for their society. It encourages users, generally civil servants, to perform different authentications on used information systems and have to remember credentials. Account management of the users poses another challenge for administrators. Single Sign-On (SSO) can be the solution by providing a service of centralized authentication and user account management. This study applies a token-based SSO architecture and uses Json Web Token (JWT) to grant permission authorities, since JWT can provide a claim process between 2 parties. Additionally, the built-in dashboard lists associated information systems to facilitate accessing for the authenticated users. This study will discuss JWT implementation on the dashboard of government information systems that implements SSO, which will generate the permission authorities securely for connected information systems on SSO.
Volume: 16
Issue: 4
Page: 1745-1751
Publish at: 2018-08-01

Evaluation of Research Standards at Ministry of Research, Technology and Higher Education with I-MR Map Control Analysis

10.12928/telkomnika.v16i4.10491
Muhammad; University of Indonesia Dimyati , Akhmad; Islamic University of Indonesia Fauzy
In order to accommodate research activities at all universities in Indonesia, the Directorate Genereal of Strengthening for Research and Development, Ministry of Research, Technology, and Higher Education (Kemenristekdikti) of the Republic of Indonesia established research quality standard. The standard includes the minimum targets that must be achieved by each University at the period of conducting the research activity. However, until now there has been no measurement to find out whether the existing standard was good enough or needs to be evaluated. Therefore, this study was conducted to measure the standards. The method used was the analysis of I-MR (Individual and Moving Range) control chart to see the performance of the standard. The results show that existing research schemes have encouraged the improvement of international publications, but have not yet maximized the production of other outputs such as textbooks, accredited national publications, intellectual property rights, and ptototypes. The result of the research was expected to be used as material for evaluation and improvement of policy to improve the quality of research standard in Kemenristekdikti.
Volume: 16
Issue: 4
Page: 1449-1456
Publish at: 2018-08-01

Designing Fuzzy Expert System to Identify Child Intelligence

10.12928/telkomnika.v16i4.7779
Muhamad Bahrul; Esa Unggul University Ulum , Vitri; YARSI University Tundjungsari
Every child is special and has her/his own unique potential. Identifying child’s potential in early age is important for teaching purpose since every child has difference intelligence and interest. Therefore children’s teaching and learning process should be delivered based on child’s interest and intelligence, instead of forcing children to excel in every subject. We propose our research to identify child’s intelligence by designing fuzzy expert system. The system works based on several input data of children’s multiple intelligences. The fuzzy expert system is developed using 25 input variables and resulted in 9 output variables. The system classifies the result based on 9 types of intelligence in human, where each exhibits different level. We produce 81 rules with fuzzy set of three different levels value (high, moderate, or low) for every kind of intelligence. The result of this research is very useful to help parents and teachers for determining their method of teaching based on children’s potential.
Volume: 16
Issue: 4
Page: 1688-1696
Publish at: 2018-08-01

Training of Convolutional Neural Network using Transfer Learning for Aedes Aegypti Larvae

10.12928/telkomnika.v16i4.8744
Mohamad Aqil; Universiti Teknikal Malaysia Melaka Mohd Fuad , Mohd Ruddin; Universiti Teknikal Malaysia Melaka Ab Ghani , Rozaimi; Universiti Teknikal Malaysia Melaka Ghazali , Tarmizi Ahmad; Universiti Teknikal Malaysia Melaka Izzuddin , Mohamad Fani; Universiti Teknikal Malaysia Melaka Sulaima , Zanariah; Universiti Teknikal Malaysia Melaka Jano , Tole; Universitas Ahmad Dahlan Sutikno
The flavivirus epidemiology has reached an alarming rate which haunts the world population including Malaysia. World Health Organization has proposed and practised various methods of vector control through environmental management, chemical and biological orientations. However, from the listed control vectors, the most crucial part to be heeded are non-accessible places like water storage and artificial container. The objective of the study was to acquire and compare various accuracies and cross-entropy errors of the training sets within different learning rates in water storage tank environment which was essential for detection. This experiment performed transfer learning where Inception-V3 was implemented. About 534 images were trained to classify between Aedes Aegypti larvae and float valve within 3 different learning rates. For training accuracy and validation accuracy, learning rates were 0.1; 99.98%, 99.90% and 0.01; 99.91%, 99.77% and 0.001; 99.10%, 99.93%. Cross-entropy errors for training and validation for 0.1 were 0.0021, 0.0184 whereas for 0.01 were 0.0091, 0.0121 and 0.001; 0.0513, 0.0330. Various accuracies and cross-entropy errors of the training sets within the different learning rates were successfully acquired and compared.
Volume: 16
Issue: 4
Page: 1894-1900
Publish at: 2018-08-01

Microwave Bandpass Filter Integrated with Notch Response for Wide-band Applications

10.11591/ijeecs.v11.i2.pp797-804
Mussa Mabrok , Zahriladha Zakaria , Nurhana Abu Hussin , Mohamad Ariffin Mutalib
This paper presents the design of wide-band bandpass filter using microstrip structure at 3-6GHz with fractional bandwidth of 66.67% based upon short-circuited stubs structure of 5th degree. In order to avoid the interference from existing system that operates in the frequency band, the folded stepped impedance resonator (SIR) was introduced to generate a narrow notch band at 5.2GHz. Pin diode is employ as switching mechanism for the notch response. This design is simulated by Advance Design System (ADS) software and using Roger Duroid 4350B with a dielectric constant of 3.48, substrate thickness 0.508mm and loss tangent 0.0019.The achieved return loss is better than 15dB and insertion loss is less than 1dB.The designed filter can be used in microwave communication systems such as wireless communication devices and military applications (radar system).
Volume: 11
Issue: 2
Page: 797-804
Publish at: 2018-08-01
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