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Journal of Telematics and Informatics

JTI
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Published by IAES Indonesia Section and Partners

ISSN : - EISSN : - DOI : -

Core Subject : Science, Engineering,

Computer Science & IT Electrical & Electronics Engineering

Journal of Telematics and Informatics (e-ISSN: 2303-3703, p-ISSN: 2303-3711) is an interdisciplinary journal of original research and writing in the wide areas of telematics and informatics. The journal encompasses a variety of topics, including but not limited to: The technology of sending, receiving and storing information via telecommunication devices in conjunction with affecting control on remote objects; The integrated use of telecommunications and informatics; Global positioning system technology integrated with computers and mobile communications technology; The use of telematic systems within road vehicles, in which case the term vehicle telematics may be used; The structure, algorithms, behavior, and interactions of natural and artificial systems that store, process, access and communicate information; Develops its own conceptual and theoretical foundations and utilizes foundations developed in other fields; and The social, economic, political and cultural impacts and challenges of information technologies (advertising and the internet, alternative community networks, e-commerce, e-finance, eâ€“governance, globalization and security, green computing, ICT for sustainable development, ICT in healthcare and education, management and policymaking, mobile and wireless communications, peer-to-peer learning, regulation of digital technologies, social networking, special user groups, the 2.0 paradigm, the WWW, etc). The journal is a collaborative venture between Universitas Islam Sultan Agung (UNISSULA), Universitas Ahmad Dahlan (UAD) and Institute of Advanced Engineering and Science (IAES) Indonesia Section.

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Articles 141 Documents

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Automated Erythrocytes Counting in Microscopic Thin Blood Smear Digital Images Naveed Abbas; Dzulkifli Mohamad; Abdual Hanan Abdullah
Journal of Telematics and Informatics Vol 3, No 2: September 2015
Publisher : Universitas Islam Sultan Agung

The Erythrocytes counting is part of the complete blood count test and it is frequently suggested by the Physician to know the number of Erythrocytes in the patient’s body. At present mostly the counting process is performed manually which is laborious, error prone and time consuming. The main purpose of this study is to use the digital image processing techniques to automate the counting process of the Erythrocytes or Red Blood Cells in Microscopic thin Blood smear digital images. The automated diagnosing gain the attention of the researchers from the last two decades because it assist the experts to reduce the burden of errors, labour and time of examination. In this regard, too much research has been performed on the automation of the counting process of the Erythrocytes but still the test demands to be done in a proper, efficient, accurate and realistic way. The proposed method achieved an average True Positive Rate (TPR) of 95%, True Negative Rate (TNR) of 5%, average accuracy of 97% and average error of 3%.

Detection and Classification of three phase Power Quality events using Wavelets Transforms and Soft Computing Techniques Abhijith Augustine; Ruban Deva Prakash; Rajy Xavier
Journal of Telematics and Informatics Vol 4, No 1: March 2016
Publisher : Universitas Islam Sultan Agung

Analysis of power quality and its related problems is of very much important for both the utilities and end users. There are a large number of concerned authorities to monitor and mitigate the power quality problems. It requires a larger amount to deliver a poor power. So by considering the global economical losses, it is very much urgent to mitigate the various problems affecting the true power. Classification of problems is equally important to mitigation. The common power quality problems occurring are voltage sag, swell, harmonics, flickers etc. Good power determines the fitness of electric power to consumer devices and appliances. It is very important to maintain the detection accuracy of power quality events throughout the operation span. This paper deals with a study based on signal processing algorithms and soft computing techniques for the detection, classification and estimation of power quality events. The literature review points toward the application of wavelet transforms with different filters for achieving feature extraction. The power quality disturbance model is simulated using Simulink toolbox. It is observed that every power quality wavelet disturbance will show unique characteristics and it is generally used to provide an adoptable classification of power quality events. Because of the non-stationary and transitory behavior of the power quality events, the classification goes on challenging and demanding. Thus the feature extraction along with artificial neural network and fuzzy logic incorporated as a powerful tool

One-Minute Derivation of The Conjugate Gradient Algorithm Muhammad Ali Raza Anjum
Journal of Telematics and Informatics Vol 4, No 1: March 2016
Publisher : Universitas Islam Sultan Agung

One of the great triumphs in the history of numerical methods was the discovery of the Conjugate Gradient (CG) algorithm. It could solve a symmetric positive-definite system of linear equations of dimension N in exactly N steps. As many practical problems at that time belonged to this category, CG algorithm became rapidly popular. It remains popular even today due to its immense computational power. But despite its amazing computational ability, mathematics of this algorithm is not easy to learn. Lengthy derivations, redundant notations, and over-emphasis on formal presentation make it much difficult for a beginner to master this algorithm. This paper aims to serve as a starting point for such readers. It provides a curt, easy-to-follow but minimalist derivation of the algorithm by keeping the sufficient steps only, maintaining a uniform notation, and focusing entirely on the ease of reader.

A Mobility Aware Schema To Lower Packet Losses For Reactive Ad Hoc Routing Protocols Ilyas Bambrik; Didi Fedoua
Journal of Telematics and Informatics Vol 4, No 1: March 2016
Publisher : Universitas Islam Sultan Agung

In an increasingly wireless world, Ad hoc networks have progressively been developed to become a suitable replacement or, at least complement to the traditional wireless networks. In contrast to the conventional wireless network, the Ad hoc network does not necessarily need a preset infrastructure to be functional. The network members move freely and arrange themselves to perform the routing operations in a distributed fashion. The kernel technology enabling such flexibility is the routing protocol. Though the absence of the infrastructure lowers the installation, configuration and maintenance cost of the dynamic networks, the mobile nodes must deal with several complex issues. Thus, managing : a) security, b) power consumption and balance, c) Quality of Service, in a distributed manner is very challenging. However, above all else, maintaining a path formed by moving particles is the most problematic task. In this paper we analyse the effect of the nodes mobility on the routing protocol performance. Then, we propose a simple schema to counter this issue.

Average Hashing for Perceptual Image Similarity in Mobile Phone Application Sam Farisa Chaerul Haviana; Dedy Kurniadi
Journal of Telematics and Informatics Vol 4, No 1: March 2016
Publisher : Universitas Islam Sultan Agung

Common problem occurs in almost all mobile devices was duplicated data or files. Such as duplicated images that often happen by event like capturing perceptually similar photos by the user, or images that shared several times in messaging applications chat groups. This common problem can be solved by manually search and remove the duplicated images one by one by the users, but better solutions is by building automated application that search perceptually similar images then provide the result to the users. We study and implementing Average Hashing and Hamming distance for perceptual image similarity into application under mobile phone platform to realize the solution for the problem. The result was very promising in speed and accuracy for finding perceptually similar images under limited resources device like mobile phone.

Data Mining Sales Optimizations Using Sequential Minimal Optimization Algorithm Dedy Kurniadi; Sam Farisa Chaerul Haviana
Journal of Telematics and Informatics Vol 4, No 2: September 2016
Publisher : Universitas Islam Sultan Agung

Tightness of business nowadays requires businessman to be able to develop their business to compete with the other companies, this study was conducted to obtain data accurate on the type of clothing combinations that are favored by the consumers to optimize sales at convection companies, using data mining methods and technique of classification this data is classify into four classes namely, well-liked, liked, enough and dislike. To solve classification problems, this study used Sequential Minimal Optimization (SMO), SMO Algorithm can solve quadratic programming problems without requiring a large matrix and to solving the optimization SMO selected from the smallest optimization in every steps. Optimum accuracy obtained in this study were obtained from Correctly Classified Instance of 80.9% from 3072 record set of well-liked classes that is the class with type of combinations clothes polo and embroidery, then the level of measurement of consistency coefficient values using kappa statistic obtained for 0.73% where the data in the class showed a consistent value, from these data type are most well-liked combinations can optimize sales by 70.3%

Design of Computer Based Signal Generator Abdelhadi Husein Aburawis; Imam Much Ibnu Subroto; Muhammad Qomaruddin
Journal of Telematics and Informatics Vol 4, No 1: March 2016
Publisher : Universitas Islam Sultan Agung

The project includes various types of signals alternative study and representation of a computer in digital format and out through the port as an outlet for the output of digital data to generate signals and electronic control circuit of the printer parallel LPTI prevailing used to generate signals. The aim of the research is to evaluate the usage of the computer including the advantage of its possibilities, capabilities in multiple signals processing, and control signal generation methods in many ways that are used to generate various signals at frequencies different capacities. The necessary software requires generating different types of signals, frequencies, and capacities. It is as well as the different software required for the purpose of controlling the electronic circuit. It has been relying on a programmatic method depends on the language of Visual Basic. In addition to the study of the physical system requirements, the analysis how to connect them with the computer and version control signals E-circle this study using speed of a transferring time for generator is Tc = 100nsec. The Speed of a computer which is used to treat ‘1000 MHz’, is got on the farthest frequency to get out from the circle is ‘2500 Hz’. It is used to different signals, sine, triangular or square in 30 samples. The sample numbers are tested. The result of this study shows that each of the sample number, input frequency, and sample time influence the results clearly. If the sample numbers increase, the accuracy of the waves increases. If the input frequency increases, the width of the wave losses. Keywords: Signal Generator, Computer, Visual Basic, Signals

Synthesis of Unequally Spaced Linear Micro Strip Rectangular Patch Antenna Array Using Improved Local Search Particle Swarm Optimization Karuna Kumari; P. V. Sridevi
Journal of Telematics and Informatics Vol 4, No 2: September 2016
Publisher : Universitas Islam Sultan Agung

Antenna array systems with low side lobe levels are essential for today wireless communication systems. This paper presents the synthesis of unequally spaced linear rectangular micro strip antenna array with minimum side lobe levels using the novel evolutionary algorithm known as improved local search particle swarm optimization (ILSPSO). ILSPSO is a modified version of particle swarm optimization (PSO), in which Gaussian distribution is used to enhance the local search of the PSO. In this paper, ILPSO is applied to optimize the positions of the micro strip antenna elements to suppress the peak side lobe level (PSLL) along with PSO and differential evolution (DE) algorithms. The steps involved in problem formulation along with design examples illustrating the performance of the ILPSO in minimizing the side lobe levels are demonstrated. A 20 and 32 element linear micro strip rectangular patch antenna (MSRPA) element are considered to show the effectiveness of the proposed method. The optimized micro strip antenna array is simulated using high frequency structure simulator (HFSS). The synthesis results demonstrate that the ILSPSO outperforms PSO and DE in terms of producing lower PSLL and convergence rate. The flexibility and ease of implementation of the ILSPSO algorithm is obvious from this paper, showing the algorithms usefulness in other array synthesis problems.

Machine Learning Approaches on External Plagiarism Detection Imam Much Ibnu Subroto; Ali Selamat; Badieah Assegaf
Journal of Telematics and Informatics Vol 4, No 2: September 2016
Publisher : Universitas Islam Sultan Agung

External plagiarism detection is a technique that refers to the comparison between suspicious document and different sources. External plagiarism models are generally preceded by candidate document retrieval and further analysis and then performed to determine the plagiarism occurring. Currently most of the external plagiarism detection is using similarity measurement approaches that are expressed by a pair of sentences or phrase considered similar. Similarity techniques approach is more easily understood using a formula which compares term or token between the two documents. In contrast to the approach of machine learning techniques which refer to the pattern matching and cannot directly comparing token or term between two documents. This paper proposes some machine learning techniques such as k-nearest neighbors (KNN), support vector machine (SVM) and artificial neural network (ANN) for external plagiarism detection and comparing the result with Cosine similarity measurement approach. This paper presented density based that normalized by frequency as the pattern. The result showed that all machine learning approach used in this experiment has better performance in term of accuracy, precision and recall.

Student Academic Performance Prediction on Problem Based Learning Using Support Vector Machine and K-Nearest Neighbor Badieah Assegaf
Journal of Telematics and Informatics Vol 5, No 1: March 2017
Publisher : Universitas Islam Sultan Agung

Academic evaluation is an important process to know how well the learning process was conducted and also one of the decisive factors that can determine the quality of the higher education institution. Though it usually curative, the preventive effort is needed by predicting the performance of the student before the semester begin. This effort aimed to reduce the failure rate of the students in certain subjects and make it easier for the PBL tutor to create appropiate learning strategies before the tutorial class begin. The purpose of this work is to find the best data mining technique to predict student academic performance on PBL system between two data mining classification algorithms. This work applied and compared the performance of the classifier models built from Support Vector Machine (SVM) and K-Nearest Neighbor (KNN). After preprocessed the dataset, the classifier models were developed and validated. The result shows that both algorithms were giving good accuracy by 97% and 95,52% respectively though SVM showing the best performance compared to KNN in F-Measure with 80%. The further deployment is needed to integrate the model with academic information system, so that academic evaluation can be easily done.

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