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Journal receives papers in continuous flow and we will consider articles from a wide range of Information Technology disciplines encompassing the most basic research to the most innovative technologies. Please submit your papers electronically to our submission system at http://jatit.org/submit_paper.php in an MSWord, Pdf or compatible format so that they may be evaluated for publication in the upcoming issue. This journal uses a blinded review process; please remember to include all your personal identifiable information in the manuscript before submitting it for review, we will edit the necessary information at our side. Submissions to JATIT should be full research / review papers (properly indicated below main title).

Journal of Theoretical and Applied Information Technology
June 2017 | Vol. 95 No.12

Title:	MRMR BA: A HYBRID GENE SELECTION ALGORITHM FOR CANCER CLASSIFICATION
Author:	OSAMA AHMAD ALOMARI, AHAMAD TAJUDIN KHADER, MOHAMMED AZMI AL-BETAR, LAITH MOHAMMAD ABUALIGAH
Abstract:	The microarray technology facilitates biologist in monitoring the activity of thousands of genes (features) in one experiment. This technology generates gene expression data, which are significantly applicable for cancer classification. However, gene expression data consider as high- dimensional data which consists of irrelevant, redundant, and noisy genes that are unnecessary from the classification point of view. Recently, researchers have tried to figure out the most informative genes that contribute to cancer classification using computational intelligence algorithms. In this paper, we propose a filter method (Minimum Redundancy Maximum Relevancy, MRMR) and a wrapper method (Bat algorithm, BA) for gene selection in microarray dataset. MRMR was used to find the most important genes from all genes in gene expression data, and BA was employed to find the most informative gene subset from the reduce set generated by MRMR that can contribute in identifying the cancers. The wrapper method using support vector machine (SVM) method with 10-fold cross-validation served as evaluator of the BA. In order to test the accuracy performance of the proposed method, extensive experiments were conducted. Three microarray datasets are used, which include: colon, Breast, and Ovarian. Same method procedure was performed to Genetic algorithm (GA) to conducts comparison with our proposed method (MRMR-BA). The results show that our proposed method is able to find the smallest gene subset with highest classification accuracy.
Keywords:	Bat-inspired algorithm, Cancer Classification, Gene Selection, MRMR, SVM.
Source:	Journal of Theoretical and Applied Information Technology 30^th June 2017 -- Vol. 95. No. 12 -- 2017
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Title:	IT ADOPTION MODEL FOR HIGHER EDUCATION
Author:	HERU NUGROHO
Abstract:	Information Technology (IT) is a critical asset for higher education institutions and support institutional strategic objectives. One of the most common problems of using ICT in education is to base choices on technological possibilities rather than educational needs. In developing countries where higher education is fraught with serious challenges at multiple levels, there is increasing pressure to ensure that technological possibilities are viewed in the context of educational needs. In the IT adoption is necessary to consider several important aspects related to these technologies, such as the direction of technological development in accordance with the strategic plan. The problems arise when the Higher Education will adopt a new technology but does not consider the current technology trends. Hype Cycles provide technology trend with a graphic representation of the maturity and adoption of technologies and applications, and how they are potentially relevant to solving real business problems and exploiting new opportunities. In this paper will propose IT adoption model for higher education base on the factor that influences IT adoption in higher education which is obtained from another research with adding a technology trend as a factor that influence. By using factor analysis with SPSS, produces five group of factors that infuluence for IT adoption in Higher Education. IT Adoption Model For Higher Education can be used by universities as a reference to adopting a new technology that is in line with the strategy that has been set with with attention to each of the factors that influence.
Keywords:	Information Technology, IT Adoption, Hype Cycle, Higher Education
Source:	Journal of Theoretical and Applied Information Technology 30^th June 2017 -- Vol. 95. No. 12 -- 2017
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Title:	FUSING DATA RETRIEVED FROM HETEROGENEOUS SOURCES TO PREDICT USER’S HEALTH
Author:	G.RAMESH CHANDRA, A.KATYAYANI,N.SANDHYA
Abstract:	The information gathered from various sources is integrated to identify the risks associated with the user’s health. The main objective of employing fusion is to produce a fused result that provides the most reliable information about the health condition of the user. The proposed research aims to assess the health status of the user based on the frequency of usage of computers and mobile. It also investigates the association between the extent of computer and mobile usage and the related health disorders like strained vision, headache and backache. The findings confirmed that the health disorders occur simultaneously among prolonged computer users and mobile users.
Keywords:	Data Fusion, Heterogeneous Data Sources, Health Disorders, Frequency Based Conditions
Source:	Journal of Theoretical and Applied Information Technology 30^th June 2017 -- Vol. 95. No. 12 -- 2017
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Title:	ENHANCED NORMALIZATION APPROACH ADDRESSING STOP-WORD COMPLEXITY IN COMPOUND-WORD SCHEMA LABELS
Author:	JAFREEN HOSSAIN, NOR FAZLIDA MOHD SANI, LILLY SURIANI AFFENDEY, ISKANDAR ISHAK, KHAIRUL AZHAR KASMIRAN
Abstract:	An extensive review of the existing schema matching approaches discovered an area of improvement in the field of semantic schema matching. Normalization and lexical annotation methods using WordNet have been somewhat successful in general cases. However, in the presence of stop-words these approaches result in poor accuracy. Stop-words have previously been ignored in most studies resulting in false negative conclusions. This paper proposes NORMSTOP (NORMalizer of schemata having STOP-words) as an improved schema normalization approach that addresses the complexity of stop-words (e.g. ‘by’, ‘at’, ‘and,’ or’) in Compound Word (CW) schema labels. Using a combined set of WordNet features, NORMSTOP isolates these labels during the preprocessing stage and resets the base-form to a relevant WordNet term, or an annotable compound noun. When tested on the same real dataset used in the earlier approach - (NORMS or NORMalizer of Schemata), NORMSTOP shows up to 13% improvement in annotation recall measurement. This level of improvement takes the overall schema matching process another step closer to perfect accuracy; while its absence exposes a gap in expectation, especially in today’s databases, where stop-words are in abundance.
Keywords:	Database Integration, Schema Matching, Data Heterogeneity, Semantic Schema Matching, Schema Label Normalization, Stop-Words
Source:	Journal of Theoretical and Applied Information Technology 30^th June 2017 -- Vol. 95. No. 12 -- 2017
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Title:	A REVIEW OF DATA QUALITY RESEARCH IN ACHIEVING HIGH DATA QUALITY WITHIN ORGANIZATION
Author:	M. IZHAM JAYA, FATIMAH SIDI, ISKANDAR ISHAK, LILLY SURIANI AFFENDEY, MARZANAH A. JABAR
Abstract:	The aim of this review is to highlight issues in data quality research and to discuss potential research opportunity to achieve high data quality within an organization. The review adopted systematic literature review method based on research articles published in journals and conference proceedings. We developed a review strategy based on specific themes such as current research area in data quality, critical dimensions in data quality, data quality management model and methodologies and data quality assessment methods. Based on the review strategy, we select relevant research articles, extract and synthesis the information to answer our research questions. The review highlights the advancement of data quality research to resemble its real world application and discuss the available gap for future research. Research area such as organizations management, data quality impact towards the organization and database related technical solutions for data quality dominated the early years of data quality research. However, since the Internet is now taking place as the new information source, the emerging of new research areas such as data quality assessment for web and big data is inevitable. This review also identifies and discusses critical data quality dimensions in organization such as data completeness, consistency, accuracy and timeliness. We also compare and highlight gaps in data quality management model and methodologies. Existing model and methodologies capabilities are restricted to the structured data type and limit its ability to assess data quality in web and big data. Finally, we uncover available methods in data quality assessment and highlight its limitation for future research. This review is important to highlight and analyse limitation of existing data quality research related to the recent needs in data quality such as unstructured data type and big data.
Keywords:	Data Quality, Data Quality Management Model, Assessment Methods, Database, Organization
Source:	Journal of Theoretical and Applied Information Technology 30^th June 2017 -- Vol. 95. No. 12 -- 2017
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Title:	PREDICTIVE ANALYSIS OF LOCALITY-AWARE STORAGE-TIER DATA BLOCKS OVER HADOOP
Author:	NAWAB MUHAMMAD FASEEH QURESHI, DONG RYEOL SHIN, ISMA FARAH SIDDIQUI, ASAD ABBAS
Abstract:	The term Big Data analytics refers to a large-scale solution for managing giant datasets in a parallel environment. Hadoop is an ecosystem that processes large datasets in distributed computing scenario. The ecosystem is further categorized into four sub-projects i.e. HDFS, MapReduce, YARN and Hadoop Commons. The Hadoop Distributed File System (HDFS) is a backbone of ecosystem, which helps storing and processing large datasets. Recently, HDFS is upgraded to heterogeneous storage-tier environment that cope with data block processing over multiple storage devices i.e. DISK, SSD and RAM. The block placement policy dispatches data blocks to the devices without calculating I/O transfer parameters and locality perspectives. Moreover, HDFS selects random Datanodes that could be located into the next rack having longer path than local rack. This increases the data block processing latency and results in a huge delay for replica management in heterogeneous storage-tier. To resolve this issue, we propose a predictive analysis that build a locality-aware storage-tier node summary and predict the most nearby available storage-tier for block job processing. The experimental evaluation depicts that the proposed approach reduces data block transfer time overhead, replica transfer time overhead and decreases node paths to an optimal accessibility over the cluster.
Keywords:	Hadoop, HDFS, Locality-aware, network distance, storage-tier.
Source:	Journal of Theoretical and Applied Information Technology 30^th June 2017 -- Vol. 95. No. 12 -- 2017
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Title:	DETECTION OF LOGICAL CLONE IN CODE USING DATA DEPENDENCY AND EXPRESSION LIST
Author:	SYED MOHDFAZALULHAQUE, V SRIKANTH, E. SREENIVASA REDDY
Abstract:	Code plagiarism is a main issue in various institutes and software industries. We don’t have a perfect approach in detecting the code copied. In various countries like INDIA, USA and UK majority of industries and institutes have gained their own tool for detection of code plagiarism. The developed tools will identify the code program similarities based on statements written in programming language. Our proposed work is to develop an approach which detects the dependencies based on data. We consider data program for tracking similarities on code. The list of expression and data dependencies are detected based on code copied. We prepared a dependency matrix which checks the dependencies of data in the program and compares with the list using efficient method.
Keywords:	Detection, Code Cloning, Method Of Matrix, List Related To Expression, Dependency Data.
Source:	Journal of Theoretical and Applied Information Technology 30^th June 2017 -- Vol. 95. No. 12 -- 2017
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Title:	SOFTWARE REQUIREMENT REUSE MODEL BASED ON LEVENSHTEIN DISTANCES
Author:	WONG PO HUI, WAN MOHD NAZMEE WAN ZAINON
Abstract:	Software reuse has always been one of the popular topic in software engineering community. It refers to the development of software by reusing components previous software development. Reusing components during the development of software reduces time and cost which could also enhance reliability and quality of the concept of reuse. In this paper, a software reuse model is established where it shows the overall process of retrieving the relevant use cases. A database is built and a prototype is developed based on the model. Levenshtein Distance algorithm is applied in computing the similarity score. A list of relevant use cases is displayed as a result. Evaluation criteria such as recall and precision are used to evaluate the result. Based on the results, the enhancement of the software reuse model has been proposed
Keywords:	Software Reuse, Use Case Diagram, Software Requirements
Source:	Journal of Theoretical and Applied Information Technology 30^th June 2017 -- Vol. 95. No. 12 -- 2017
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Title:	AWARENESS AND ATTITUDES TOWARD IT GOVERNANCE: EMPIRICAL STUDY
Author:	UKY YUDATAMA, ACHMAD NIZAR HIDAYANTO, BOBBY A.A. NAZIEF
Abstract:	This study aims to examine in more depth about how, why awareness and attitudes towards the implementation of IT governance is very important, so it can affect the performance of an organization or company. The methods used in this study began with literature review and interviews with some experts in their field, 4 from academics and 2 practitioners. To strengthen this research, we have distributed 100 questionnaires, but 96 respondents actively provided feedback, then analyzed and validated using a correlation test (r). To understand awareness and attitudes towards IT Governance, there are several factors that can be used. As for factors such as; Benefits, risks, opportunities and obstacles. These factors are very important and relate entirely with awareness and attitudes. By knowing these factors, all parties involved in IT Governance become easy to understand, then awareness and attitude will grow from itself, so as to improve performance and ultimately organizational goals can be achieved optimally as expected. The results obtained from this research indicate that the benefit factor and opportunity factor have more value, while the risk factor and constraint factor is smaller. In order for the implementation of IT Governance to run properly, it is necessary to be encouraged in understanding the knowledge and knowing the implementation of IT Governance that is being implemented.
Keywords:	Awareness; Attitude; Implementation; Factors; IT Governance
Source:	Journal of Theoretical and Applied Information Technology 30^th June 2017 -- Vol. 95. No. 12 -- 2017
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Title:	KALMAN STABILIZATION UNDER CHANNEL DIVERSITY IN MIMO-OFDM SYSTEM
Author:	G. RAJENDER, DR.T. ANILKUMAR, DR.K.SRINIVASA RAO
Abstract:	Signal estimation and its performance has always remained a challenge for wireless communication society. New methods to consider channel diversity and spectrum usage were proposed in past. This paper present a new approach to interference controlling, With a proposal for control of resources, to achieve the goal of increasing performance in the allocation system, using the interference conditions. Approach to control overlap in the framework of coordination and indiscriminate accessing for multiple users communication is proposed. The proposed approach develops a correlation method for resource allocation in on a multi path interference condition for faded channel condition based on the space frequency and non-stationary domain estimation.
Keywords:	Kalman Stabilization, MIMO-OFDM, Channel Diversity.
Source:	Journal of Theoretical and Applied Information Technology 30^th June 2017 -- Vol. 95. No. 12 -- 2017
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Title:	BIO-MEDICAL LITERATURE RETRIEVAL FROM MIXED LITERATURE BANK WITH THE AID OF MULTI KERNEL FUZZY C-MEANS TECHNIQUE (MK-FCM)
Author:	THAYYABA KHATOON MOHAMMED, DR. A.GOVARDHAN, DR.H.S.SAINI, DR RISHI SAYAL
Abstract:	In the apparent, biomedical literature will be retrieved starting with the mixed literature articles, utilizing Multi-Kernel Fuzzy c Means (MK-FCM) clustering technique. Literature retrieval or document retrieval is an action that utilization professional techniques for medically examine papers retrieval, the report card also different information to move forward research and practice. In the work, the biomedical query article is made also preprocessing system may be utilized and there would two sorts of preprocessing to be specific stop words removal and stemming. Then afterward those executions for preprocessing the retrieval techniques, for example, vector space modeling and retrieval modeling is utilized. In the vector space modeling the term frequency and inverse frequency measure may be broken down after that on retrieval modeling the SMART and BM25 standard models used to furthermore retrieve the literature. Behind this Multi-Kernel Fuzzy c Means (MK-FCM) technique is utilized for clustering the literature. In this differentiate kernel function named as FCM, Linear FCM, Quadratic FCM and Composite kernel function will be investigated to several measuring tests. Those biomedical query article databases where brain tumor, breast cancer, kidney stone and neovascularization is clustered. For single, randomly two, randomly three and overall four types of input biomedical documents the precision of the composite kernel function is 90% and recall of composite kernel function is 87% were compared with different strategies and it progresses the level best. By using these techniques, the retrieval performed better from other techniques.
Keywords:	Biomedical literature, Multi-Kernel Fuzzy c Means (MK-FCM) clustering, Composite kernel function, Linear FCM and Quadratic FCM.
Source:	Journal of Theoretical and Applied Information Technology 30^th June 2017 -- Vol. 95. No. 12 -- 2017
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Title:	MESURING THE EFFICENY OF USING HADOOP TO ANALYZE BIG DATA- A CASE STUDY ON TWITTER DATA SET
Author:	YOUSEF K. SANJALAWE, MOHAMMED ANBAR
Abstract:	In last decades, the continuous enhancements of computational power have produced a massive data flow. Big data has been becoming more understandable as well as becoming more available. For instance, the famous online social networks, such as Facebook, and twitter, serve about 560 billion page views everyone’s month. They also store new number of images near 3 billion each one month. This research emphasizes the solution and importance of big data problems using cloud computing (CC). Knowledge implanted in big data can be generated by personal computers PCs, mobile devices, and sensors, but it requires spending millions or billions of dollars in order to solve knowledge and information extraction problems to make suitable and critical decisions. In this research, we use Hadoop tool to analyze the big online data set with 8 GB size. The results show the importance of cloud approach to analyze the huge data with less efforts, cost, and time.
Keywords:	Big Data; Big Data Analytics; Cloud Service; Hadoop; Analyze Data Of Twitter.
Source:	Journal of Theoretical and Applied Information Technology 30^th June 2017 -- Vol. 95. No. 12 -- 2017
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Title:	A HYBRID WEIGHT-BASED AND STRING DISTANCES USING PARTICLE SWARM OPTIMIZATION FOR PRIORITIZING TEST CASES
Author:	MUHAMMAD KHATIBSYARBINI, MOHD ADHAM ISA, DAYANG NORHAYATI ABANG JAWAWI
Abstract:	Regression testing is concerned with testing the modified version of software. However, to re-test entire test cases require significant cost and time. To reduce the cost and time, higher average percentage fault detection (APFD) rate and faster execution to kill fault mutant are required. Therefore, to achieve these two requirements, an improvement to existing Test Case Prioritization (TCP) technique for a more effective regression testing is offered. A weight-hybrid string distance technique and prioritization using particle swarm optimization (PSO) is proposed. Distance between test cases and weight for each test case, and hybridization of both values for weight-hybrid string distance are calculated. This experiment was evaluated using Siemens dataset. Result obtained from this experiment shows that weight-hybrid string distance is capable of improving APFD values whereby APFD value for hybrid TFIDF-JC is equal to 97.37%, which shows the highest improvement by 4.74% as compared to non-hybrid JC. Meanwhile, for percentage of test cases needed to kill 100% fault mutants, hybrid TFIDF-M yields the lowest value, 22.88%, which shows a 76% improvement as compared to its non-hybrid string distance.
Keywords:	Software testing, Regression testing, Test case prioritization, Particle Swarm Optimization, String Distance
Source:	Journal of Theoretical and Applied Information Technology 30^th June 2017 -- Vol. 95. No. 12 -- 2017
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Title:	ENSEMBLE MULTI-LABEL TEXT CATEGORIZATION BASED ON PYRAMIDAL CLUSTER MEMBERSHIP APPROACH
Author:	J. STALIN JOSE, DR. P. SURESH
Abstract:	Text Categorization is an interesting field in the study of Textual Data Mining. It has attracted an increasing popularity with its explosive growth of textual documents. The documents are connected with exclusive multitude categories i.e sports, medical, health, and Olympic Games). Text categorization paves different opportunities for creating multi-label learning approaches that specifically to textual data. Text mining defines the processes of discovering useful knowledge patterns from textual data. This is one of the factors followed in automated text categorization. It is practiced by developing novel machine learning approaches. Anyhow, the ML model generates low expressivity. The ML model established using Train-Test scenario. In case the existing model is found deficient, the Train-Test-Retrain is developed which is time consuming process. In this paper, we proposed “Pyramidal Cluster Membership Approach (PCMO)”. It works in two models namely, training and testing model. The training model comprised of four phases, Pyramid-Fuzzy Transmutation, Novel k-edge classifier, Cluster to Category mapping and finding the boundaries. These estimated boundaries are applied on new textual data and the categories are assigned. Experimental results on Freebase dataset show that the proposed approach based on pyramidal membership method can achieve better classification accuracy than the traditional approaches especially that includes over-fitting document categories.
Keywords:	Textual Data Mining, Text Categorization, Membership Functions, Pyramid Structures And Machine Learning Models
Source:	Journal of Theoretical and Applied Information Technology 30^th June 2017 -- Vol. 95. No. 12 -- 2017
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Title:	SPECTRUM SHARING AND COMPATIBILITY BETWEEN THE INTERNATIONAL MOBILE TELECOMMUNICATION-ADVANCED AND DIGITAL BROADCASTING IN THE DIGITAL DIVIDEND BAND
Author:	MOHAMMED B. MAJED, THAREK A. RAHMAN
Abstract:	The International Telecommunication Union for Radiocommunication (ITU-R) became involved with the spectrum allocation for next generation mobile communication services in World Radio Communication conference 2007 (WRC- 07). The reason is to minimize the adjacent channel interference between Mobile service and DVB-T system within the same geographical area. Therefore, this paper investigates the spectrum sharing requirements such as separation distance and studies the compatibility between Mobile services (IMT-Advanced) and Digital Video Broadcasting – Terrestrial (DVB-T) in the 790 to 862 MHz frequency band. This paper also involves the studies of propagation characteristics within this band which can provide better coverage. Possibility of coexistence and sharing analysis were obtained by taking into account the detailed calculations of the path loss effect by using the practical parameters of DVB-T and Mobile service. The interference has been analyzed and simulated for suburban environment in different channel bandwidths for Mobile service at 5MHz and 20MHz, and in different transmitted power for Digital Video Broadcasting – Terrestrial. The best separation distance between these two systems found are 4.65 Km and 3.42 Km for bandwidth of 5MHz and 20 MHz respectively.
Keywords:	DVB-T, IMT-Advance, Propagation model, Adjacent Channel Interference, Separation Distance
Source:	Journal of Theoretical and Applied Information Technology 30^th June 2017 -- Vol. 95. No. 12 -- 2017
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Title:	COMPARISON OF TARGET PROBABILISTIC NEURAL NETWORK (PNN) CLASSIFICATION FOR BEEF AND PORK
Author:	LESTARI HANDAYANI, JASRIL, ELVIA BUDIANITA, WINDA OKTISTA, RIZKI HADI, DENANDA FATTAH, RADO YENDRA, AHMAD FUDHOLI
Abstract:	This research focuses on image recognition of beef and pork. Beef as an example of halal food, while pork as haram food, especially for Muslims. This study used PNN classification and feature extraction methods. These images show some fundamental differences between pork and beef which based on colors and texture. Color was extracted by HSV model, otherwise texture extracted with 3 methods. These methods were Gabor, Principle Component Analysis (PCA) and Local Binary Pattern (LBP). Performance comparison of these methods was measured from the target accuracy of classification. Experiments conducted on 100 images of beef, pork and mixed, with attention to smoothing parameter (spread value/) in PNN and distribution data training and data testing. The best spread value obtained 10 for Gabor+HSV+PNN and LBP+HSV+PNN, but PCA+HSV+PNN was 108. The mixed meat was recognizable by PCA+HSV+PNN and LBP+HSV+PNN equal to 100%. The highest classification performance was achieved by PCA+HSV+PNN. This method can be used to distinguish between meat of permitted food and prohibited food. Mixing pork with beef would be prohibited food for Muslims and other peoples.
Keywords:	Image Recognition; Local Binary Pattern (LBP); Principle Component Analysis (PCA).
Source:	Journal of Theoretical and Applied Information Technology 30^th June 2017 -- Vol. 95. No. 12 -- 2017
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Title:	AUTOMATED SEMANTIC QUERY FORMULATION USING MACHINE LEARNING APPROACH
Author:	RABIAH A.KADIR, ALIYU RUFAI YAURI
Abstract:	Search engines such Yahoo and Google among others has played significant role Web data access. However these search engines has limitations. These search engines are based on a keyword search which lacks semantics in the retrieval process. To cope with the Limitations of current search engines, Semantic Web was introduced. Semantic Web enables retrieval of data on the Web semantically. In semantic Web, data is standardised in a format that enables retrieval of such data semantically. But Semantic Web also has challenges where retrieval requires complex structured query such as SPARQL which is not simple are using Google like natural language query. This paper presents an approach of automatic semantic query formulation that enables retrieval of semantically structured data using natural language. The proposed approach is based on using machine learning and the result has shown improvement of 17.4% compared to existing approach in FREyA in terms of effectiveness formulated natural language queries to structured query.
Keywords:	Semantic Web, Machine learning, ontology, Quran.
Source:	Journal of Theoretical and Applied Information Technology 30^th June 2017 -- Vol. 95. No. 12 -- 2017
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Title:	SPECTRAL H2 FAULT ESTIMATION OBSERVER DESIGN BASED ON ALLOCATION OF THE CORRECTION EFFECT
Author:	EVGENY I. VEREMEY, YAROSLAV V. KNYAZKIN
Abstract:	The paper is devoted to problem of additive fault estimation observer design for LTI plants with scalar measurement and external disturbance with the known spectral structure. The filter with the calculated parameters should enhance such performances as rapidity of the fault estimation and its insensitivity to the polyharmonical disturbance signal with the certain central frequency, provided by the special filter, generating the corrective signal. The specific spectral approach of H2 optimization in frequency domain, based on the polynomial factorization, is applied with the aim to improve computational effectiveness of the synthesis. Some theoretical aspects are discussed and numerical algorithm for practical implementation is formulated. Their effectiveness is demonstrated by the numerical example with implementation of MATLAB package.
Keywords:	Linear-quadratic control, H2 optimal control, stability, fault estimation.
Source:	Journal of Theoretical and Applied Information Technology 30^th June 2017 -- Vol. 95. No. 12 -- 2017
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Title:	ASSESSING THE EFFECTIVENESS AND USABILITY OF USING PAIR PROGRAMMING TO IMPROVE PROGRAMMING LANGUAGE LEARNING, PRODUCTIVITY, AND CODE QUALITY
Author:	ZAID T. ALHALHOULI, FARHAN M Al OBISAT, TAMARA E. ALSHABATAT, TAMADOR I. ALRAWASHDEH
Abstract:	Programming is a major challenge faced by universities students at different levels. A significant learning outcome that emerged in recent years is working in teams, wherein two programmers can engage in pair programming to work on a single task as a group. This study examined the usability and effectiveness of using pair programming. We also evaluated the effects of pair programming on student results, time consumed, and number of errors, Big-O notation, and time complexity. The mixed method approach was applied by formulating a questionnaire and three different projects. We applied a novel strategy for creating pairs of students from different levels and courses in Tafila Technical University. Results indicated that pair programming is feasible and effective for educational purposes. Positive results were also obtained for programming learning, time, performance, and code quality.
Keywords:	Pair Programming Experience, Collaborative Learning, Teaching Methods, Usability, and Team Performance.
Source:	Journal of Theoretical and Applied Information Technology 30^th June 2017 -- Vol. 95. No. 12 -- 2017
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Title:	TRAFFIC LIGHT MANAGEMENT SYSTEM BASED ON HAMILTONIAN ROUTING TECHNIQUE
Author:	ADNAN A. HNAIF, AMNAH EL-OBAID, NANCY AL-RAMAHI
Abstract:	Traffic congestions are recognized as a major problem in the modern urban cities. The Hashemite Kingdom of Jordan is considered as one of the top countries worldwide that is suffering from the traffic jam problem due to its old infrastructure. The current traffic light signals system in Jordan is still controlled by the fixed timers. Therefore, this research develops an intelligent Traffic Light Management System Based on the Hamiltonian Routing Technique (TLBH) and on the Decision Support System (DSS) in order to execute a proper action. Hence, this research develops a system can that be used to minimize the waiting time on the traffic signals for vehicles, which can in return lead to the reduction of the traffic congestion incurred by the vehicles. This research is comprehensive to many scenarios, where three of these scenarios are listed in this research and are implemented by the system by using the MATLAB programming language; based on specific rules. According to these sufficient testing scenarios, the simulation result shows significant improvements in the TLBH technique in comparison with the current traffic system. The proposed technique has the minimum total and waiting time in all scenarios compared to the current traffic system.
Keywords:	Traffic light management system, routing protocols, Hamiltonian routing technique.
Source:	Journal of Theoretical and Applied Information Technology 30^th June 2017 -- Vol. 95. No. 12 -- 2017
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Title:	A PROPOSED MODEL OF M-LEARNING FOR TECHNICAL AND VOCATIONAL EDUCATION TRAINING (TVET) STUDENTS
Author:	SYAZWANI AZMI, SITI FADZILAH MAT NOOR, HAZURA MOHAMED
Abstract:	Latest educational technology that called mobile learning or m-learning is a new style of learning as the development of mobile technology which can help to hold attention and make students more on self-study at anywhere and anytime. The paper focuses on a proposed model of m-learning for Technical and Vocational Education and Training (TVET) students in Malaysia. Development of the model is based on the user requirements from the TVET students in accordance to three aspects; device, user and social technology. The proposed model will be used as a guideline in the development of m-learning application which can improve teaching and learning quality and also motivate students to have interest on the learning.
Keywords:	Mobile Technology, Education Technology, Mobile Learning, Long-Life Learning, TVET
Source:	Journal of Theoretical and Applied Information Technology 30^th June 2017 -- Vol. 95. No. 12 -- 2017
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Title:	TAXONOMY BASED FEATURES IN QUESTION CLASSIFICATION USING SUPPORT VECTOR MACHINE
Author:	ANBUSELVAN SANGODIAH, ROHIZA AHMAD, WAN FATIMAH WAN AHMAD
Abstract:	One of the areas in text mining which is text classification has attracted much attention in various industries and fields lately. This is because the text classification has the ability in labelling text documents to one or more pre-defined categories based on content similarity. As text classification emphasizes on document level, question classification works at finer level such as sentence and phrase. Several studies on question classification in respect to Bloom taxonomy to measure cognitive level of learners in higher learning institutions have been carried out in the past. But, existing feature types in the past work may work reasonably well on data sets consisting of questions that are too specific to one particular field or area which will result in having multiple classifiers to be built for questions involving various fields or areas. Certainly, feature types play an important role in improving the accuracy of classifier. Past related work emphasizes on feature types such as bag of word (BOW) and syntactic analysis in question classification. In this study, a new feature type named taxonomy based is proposed to improve the accuracy of question classification for data sets having questions from various fields. The performance of question classification using the new feature type between data sets consisting of questions from specific and various areas will be compared. Support Vector Machine classifier will be used as it is known for high accuracy in text classification. The outcome of this study shows that the taxonomy based features has the ability in improve the accuracy of classifier involving data sets of questions from various fields.
Keywords:	Feature Type, Question Classification, Support Vector Machine, Bloom Taxonomy, Bag-Of-Words
Source:	Journal of Theoretical and Applied Information Technology 30^th June 2017 -- Vol. 95. No. 12 -- 2017
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Title:	PROOFS OF IMPLICATIONS INVOLVING QUANTIFIERS DISTRIBUTION OVER LOGICAL OPERATORS
Author:	MAHER A. NABULSI, NESREEN A. HAMAD
Abstract:	Mathematics is considered the base for computer science. In particular, discrete mathematics is commonly used in many disciplines of computer science. One of the main topics that are discussed in discrete mathematics is quantifiers and their relations with logical operators. Accordingly, this paper proposes a new method to prove the validity of some implications involving quantifiers and logical operators. The proposed method is based on the idea of showing that whenever the premise of the implication is true, the conclusion cannot be false (must be true), so the implication is valid. On the other hand, if the conclusion can be false then the implication is not valid.
Keywords:	Predicate logic, Propositional logic, Quantifiers and Logical operators, Validity of implications
Source:	Journal of Theoretical and Applied Information Technology 30^th June 2017 -- Vol. 95. No. 12 -- 2017
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Title:	ANALYSIS OF SUCCESS FACTORS IN THE IMPLEMENTATION OF ERP SYSTEM IN RESEARCH INSTITUTE
Author:	INDRA BUDI, HABIBUL RAFUR
Abstract:	Organizations must be able to determine success factors in adopting and implementing Enterprise Resource Planning (ERP) system to get benefit as much as possible. Different kind of organization may be needed different success factors in implementing ERP system. Purpose of this research is to analyze the relationship between success factors and success indicators for implementation of ERP system in research institute. This research contributes to identify which the success factors are relevant for the implementation of ERP for research institute. This research uses three models, namely DeLone & McLean IS Success Model, Technology Acceptance Model 2, and the success factors in project management of ERP systems implementation. These models include variables that can indicate success factors and their relationship in implementation of ERP system. The analysis technique that used are descriptive statistics and correlation testing. This research uses National Nuclear Energy Agency in Indonesia, namely BATAN, as case study. This research finds that the success factors for the implementation of ERP are system quality, image, result demonstrability, internal support, and software selection. Those factors can affect the success indicators through an intermediary factor, namely perceived usefulness.
Keywords:	D&M IS Success Model, TAM2, project management success factors, ERP System Implementation, Research Institute
Source:	Journal of Theoretical and Applied Information Technology 30^th June 2017 -- Vol. 95. No. 12 -- 2017
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Title:	THE INTERACTION OF VEHICULAR NETWORKS ONTO AN AGILE PLATFORM SCHEME FOR SMART CITIES MANAGEMENT
Author:	AYOUB BOUROUMINE , ABDELILAH MAACH , DRISS EL GHANAMI
Abstract:	The Opportunistic Vehicular Communications did open new research fields, for the smart cities connectivity development and the vehicular cloud computing in general, that benefits the smart systems, applications and data collectors existing in the City. In this paper, we propose an Agile platform combining the usage of Smart Applications and Vehicular Communications in the Internet of Things (IoT); the Agile platform represents a case study of Internet of Things-related technologies that deploys multiple applications and interfaces to interact with different "Things" by deploying different communication technologies. In this work, we propose the utilization and evaluation of VANETs Networks that represent one of the existent communication tools in a smart city, this network will be deployed by the Agile platform to exchange specific types of informative data, thought there are other communication tools available for the Agile Platform, but, due to its flexibility and availability in a smart city, we are more interested into the VANETs Networks and how the Agile Platform may benefit from this network. In this paper, we describe the architecture and the components of the Agile Platform, how it interacts with other systems, users and servers part of the city, as well as the evaluation of VANET Networks deployment by the Agile Platform for an end-to-end communication.
Keywords:	Agile Platform, Vehicular Networks, Smart City, Smart Applications.
Source:	Journal of Theoretical and Applied Information Technology 30^th June 2017 -- Vol. 95. No. 12 -- 2017
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Title:	DYNAMIC ENERGY OPTIMIZATION TECHNIQUE IN MOBILE CLOUDLET FOR MOBILE CLOUD COMPUTING USING EFFECTIVE OFFLOADING ALGORITHM
Author:	P. PRIYA, DR.S.P.SHANTHARAJAH
Abstract:	In recent days, mobile applications are turning to be computationally intensive mainly due to its advancement, developing convenience, sophistication and reliability of the Smart phones. Mobile Cloud Computing (MCC) approach is utilized to enable mobile users in order to receive the advantages of cloud computing in a friendly manner through significant strategy for meeting the demands of the industrial requirement. However, the limitation of the device capacity and wireless bandwidth had leads to several issues such as latency delay, additionally energy waste and poor QoS while deploying MCC. To address these obstacles, we propose dynamic energy optimization in mobile cloudlet with offloading algorithm. It focuses on resolving the additional energy waste during wireless communication with minimum response time and moreover, it provides a unique approach with quality of experience/ quality of service that avoids the wastage of energy when mobile users are tolerating with complicated and unstable networking surroundings. The proposed energy optimization technique in terms of hardware (RAM & Display unit) as well as software components Wi-Fi for saving energy consumptions and decrease response time for mobile devices, clones and dynamic cloudlet. The proposed offloading algorithm is developed to decide which section offloaded can be done or whether clone or cloudlet in the devices while performing the task offloading for dynamic execution in MCC. The experimental evaluation of the Smart phones and Java server in the cloud are performed. It proved that proposed approach have saved the energy for enhancing the battery life time and improved the overall performances. The obtained results are efficient and effective for obtaining the better network type, data sizes, work load structure, computational time and energy optimization are better than the existing systems in MCC.
Keywords:	Mobile Cloud Computing (MCC), Dynamic Energy Optimization, Offloading Algorithm, Dynamic Cloudlet And Energy Model
Source:	Journal of Theoretical and Applied Information Technology 30^th June 2017 -- Vol. 95. No. 12 -- 2017
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Title:	DEVELOPING A THEORETICAL MODEL FOR BAHRAINI CITIZEN’S INTENTION TO ADOPT WEB 2.0 IN E-GOVERNMENT OF KINGDOM OF BAHRAIN
Author:	REEM AL-KAABI, BATOOL EBRAHIM, SHAHRABAN AL-WEJDANY, JEHAD MOHAMMED, FATIMA ALI
Abstract:	Most of the governments worldwide using the Internet to deliver services to their citizens. The term e-government become a universal phenomenon. Its focus on serving the citizens in efficient ways, which satisfy their needs. This done through providing government services and information on the Internet which allowed the citizens to communicate with them anytime and anywhere away from the traditional communication channels. As the main goal of e-government is toward more transparent relations with user, most of government adopt web 2.0 technologies to increase their interaction, participation and transparency with their users. Toward this point, this research based on a quantitative research approach where the principle inquire about procedure depends on the aftereffects of a questionnaire. Through the questionnaire, a proposed model was verified so as to differentiate factor affecting Bahraini citizens’ Intention to adopt the web 2.0 technologies in e-government of Kingdom of Bahrain. The model created was tested with 313 citizens and it was exposed that three factors (ease of used, usefulness and social influence) have significant effect on intention while the other don’t. The outcomes of this research adds to existing literature with regards to citizens’ Intention to adopt the web 2.0 technologies in e-government services through the developed model, explaining the context of Kingdom of Bahrain that can be utilized to be compared with other similar nations. On the hand the results of this research can help other professionals to use some of our results to find more factors that may affect citizens’ Intention to adopt the web 2.0 technologies in e-government services.
Keywords:	Web 2.0, Kingdom Of Bahrain, Intention, E-Government, Government 2.0.
Source:	Journal of Theoretical and Applied Information Technology 30^th June 2017 -- Vol. 95. No. 12 -- 2017
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