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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
July 2020 | Vol. 98 No.13

Title:	INTELLIGENT PERSONALIZED SYSTEM FOR ENHANCING THE QUALITY OF LEARNING
Author:	DALIA HASSAN AHMED HASSOUNA, AYMAN E. KHEDR, AMIRA M. IDREES, AHMED I. ELSEDDAWY
Abstract:	This study proposes an approach for studentsÃ¢â‚¬â„¢ learning style personalization. The study presents both the importance and the theoretical basis of learning styles. One of these perspectives is how self-reported learning style inventories are controversial, while others view learning styles as strategies that can be adjusted to specific tasks and conditions. To determine the efficacy of the proposed approach, an experiment has been applied and a set of Canadian Institute College students have been examined. This study concludes that we need to offer alternative ways to connect various learning styles when teaching the university students which would enable the teaching process to use different learning approaches and activities which would lead eventually to enhancing the learning process.
Keywords:	Personalization; Correlations; Learning Style Detection
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2020 -- Vol. 98. No. 13 -- 2020
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Title:	MEASURING RIPPLE EFFECT OF NATURAL LANGUAGE REQUIREMENTS CHANGE FOR ULS DYNAMIC REQUIREMENTS
Author:	AHMED SAFWAT ALY , MOHAMED BADR SENOUSY , ALAA M.RIAD
Abstract:	Ultra Large Scales Systems (ULS) or Ecosystems are growing dramatically alongside their interactions and dependencies among other system components, change management needs new tactics. As consider one change or more in ULS requirements may result in a lot of side effects in other running or planned requirements that could be called Ã¢â‚¬Å“Ripple EffectÃ¢â‚¬Â. Different ULS elements are affected in this type of environments varying from RE workers, Change Requesters and Involved parties those can be called Ã¢â‚¬ËœCrowed SourcingÃ¢â‚¬Â contributors in ULS environment. To challenge such problems, in this paper, we suggest a new methodology for requirements change evolution to able to measure the impact of several changes on ULS requirements which are represented by a Natural Language utilizing Similarity models. This paper reports on initial results of such an empirical study of Requirements change that led to ripple effects across an entire ULS environment, our case study around one of ecosystems for ERP with around 4480 stored requirement statements and closed to around 22 connected subsystems. We have used Natural Language Processing (NLP) and Similarity Models to support the model
Keywords:	ULS, Requirements Engineering, NLP, Similarity Models, Change Management
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2020 -- Vol. 98. No. 13 -- 2020
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Title:	EDUCATIONAL ROBOTICS BASED ON ARTIFICIAL INTELLIGENCE AND CONTEXT-AWARENESS TECHNOLOGY: A FRAMEWORK
Author:	DALIA KHAIRY, RANIA A. ABOUGALALA, MARWA F. AREED, SAFAA M. ATAWY, SALEM ALKHALAF, MOHAMED A. AMASHA.
Abstract:	Educational Robotics' (ER) use of Artificial Intelligence (AI) ranges from (Science, Technology, Engineering and Mathematics) STEM area, logical mathematical, debugging, LEGO robots, and a lot more. There is an urgent need for (ER) research on policy and use. However, this paper presents a framework for the representation of knowledge about using Educational Robotics and Context-Awareness technology in the learning environment. This framework enables smart class performance in higher education. The purpose of this study presents a new strategy in many aspects. Expanding and optimizing the studentsÃ¢â‚¬â„¢ answers and develop the users' participation in communication. The framework introduces a context controller system on the mobile terminal to connect and prepare the data from the robotics indicators. Additionally, it mixes different AI identification services in the cloud to obtain the context information through investigating and understanding the data. We also present a vision of use robotics and context-aware technology in the learning environment to improve and optimize the most benefits from the context information.
Keywords:	Educational Robotics, Artificial Intelligence, Context-aware Technology, E-learning.
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2020 -- Vol. 98. No. 13 -- 2020
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Title:	EMR FOR OBSTETRIC EMERGENCY DEPARTMENT AND LABOUR WARD IN JORDAN UNIVERSITY HOSPITAL
Author:	JANNAT FALAH , SALSABEEL F. M. ALFALAH , SAEED HALAWANI , MOHAMMAD ABULEBBEH , NADIA MUHAIDAT
Abstract:	The use of computer technology of all forms is spreading quickly and widely across all medical specialties, including its use in medical record keeping in the form of Electronic Medical Records (EMR), for it has been realized that this provides several benefits over traditional paper based record systems. Tablet based applications are particularly useful in this area as they offer portability, and support the needs of dynamic medical environments. This paper describes the development of a purpose designed novel tablet based EMR for the Obstetric Emergency Department (OED) and Labour Ward (LW) of a hospital where electronic medical records are only partially implemented at present. The pre-design stage in the form of a thorough investigation of the currently used system, its shortfalls, and determination of the usersÃ¢â‚¬â„¢ requirements for the proposed new system was followed by defining a set of aims that the new system should realise. This was taken to be the basis for designing and developing the tablet based EMR. After development, the tablet-based EMR was then evaluated by its potential user groups, showing that it has the potential to improve record keeping in the obstetric department by overcoming several shortfalls of the traditional paper record system, and adding benefits such as portability, more efficient data entry and retrieval, and streamlining the patient journey through the department.
Keywords:	Electronic Medical Records, Obstetrics, Tablet, Emergency Department, Labour Ward
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2020 -- Vol. 98. No. 13 -- 2020
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Title:	E-WOM, TRUST, USEFULNESS, EASE OF USE, AND ONLINE SHOPPING VIA WEBSITES: THE MODERATING ROLE OF ONLINE SHOPPING EXPERIENCE
Author:	BILAL ENEIZAN , ABDALLAH ALSAAD , ABDELBASET ALKHAWALDEH , HASSAN N RAWASH, ODAI ENAIZAN
Abstract:	Purpose: This research contributes towards the development of Electronic Commerce Literature in two ways that are: in the first phase it focuses upon the influence of usefulness, ease of use, electronic mouth of words, trust on online shopping, in the second phase it tested the effect of online experience as a moderation on the relationship between trust and attitude towards online shopping in the context of Jordan. Design/methodology/approach: The structural model was assessed using PLS bootstrapping procedures. The hypotheses were assessed based on path coefficients and their significance level. Hypotheses H1, H2, H3, H4 and H5 were assessed based on the baseline model. Meanwhile, hypothesis H6 was assessed based on the moderated model. Findings: The results revealed that the relationship between ewom and trust was positive and significant, providing empirical support for hypothesis H1. Similarly, the relationship between ease of use and trust was positive and significant therefore providing support for hypothesis H2. Contrary to the expectation of hypothesis H3, the results also indicated that the relationship between usefulness and trust was at the opposite direction and not significant, thereby hypothesis H3 was rejected. The results also revealed that the relationship between trust and online purchasing was positive and significant providing empirical support for hypothesis H4. The moderated model was designed to estimate the moderating effect of online experience on the relationship between trust and online purchasing as stated in hypothesis H5. The results indicated that H5 was rejected. The result are discussed in line with the previous literature and the limitations and future research areas were discussed too. Originality/value: This study contributes to the literature on the adoption of online shopping by the consumers of developing countries. In addition, this paper examines the effect of E-WOM, trust, usefulness, and ease of use on online shopping via websites with the moderating role of online experience
Keywords:	E-WOM, Trust, Usefulness, Ease Of Use, Online Shopping, Online Shopping Experience
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2020 -- Vol. 98. No. 13 -- 2020
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Title:	THE ENHANCEMENT OF COLLABORATIVE LEARNING THROUGH INTEGRATED KNOWLEDGE MANAGEMENT SYSTEMS: E-LEARNING MODEL
Author:	OKFALISA , SALMAINI Y , AB RAZAK C.H , B. PRANGGONO
Abstract:	There are still a few educational platforms that apply a Knowledge Management System (KMS) concept in conducting its operational work. In addition, several obstacles associated with e-learning implementation trigger the in-effectiveness of collaborative learning. However, the concept of Knowledge Management (KM) from a Sharia perspective has significant implications for education systems. This research, therefore, explored the relevance of the Learning Management System (LMS), KM theory, and Sharia education perspective on the development of the Integrated Knowledge Management System (IKMS) Framework. The IKMS components and structures are literature reviewed and then qualitatively justified through the focus group discussion which involved some students, lectures, and experts from two Sharia-based Universities in Indonesia. To verify and test the framework, an IKMS-Edu system was developed by focusing on the adoption of a controlling agent system in the online discussion. Herein, filtering and summarization technology was embedded into IKMS-Edu towards a smart controlling agent. This agent adopted the operational work of IKMS-Edu framework leveraging in four constructs activities viz., knowledge creation and knowledge acquisition (construct 1), knowledge organization and knowledge storage (construct 2), knowledge dissemination and knowledge retrieval (construct 3), and knowledge evaluation and feedback (construct 4). To date, the statistical evaluation of the IKMS-Edu systemÃ¢â‚¬â„¢s acceptance is conducted by disseminating the questionnaires. The mean scores revealed 40.45% of the respondents strongly agreed, and 42.18% agreed on the proposed framework and prototype system thus the framework aided in performing the IKMS during the collaborative learning activities. As such, this evidence provides the strong support that IKMS-Edu significantly enhanced the effectiveness of collaborative learning by considering the Sharia values of trust, knowledge, virtue, psychosocial, and civilization development into knowledge management activities.
Keywords:	Knowledge Management System, Learning Management System, E-Learning, Online Discussion, Integrated Knowledge Management
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2020 -- Vol. 98. No. 13 -- 2020
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Title:	PRACTICAL FRAMEWORK FOR SOFTWARE INTEGRITY MEASUREMENT BASED ON STATIC ANALYSIS
Author:	SHAREFA MURAD
Abstract:	Quality metrics technology is a disciplined approach used to evaluate, predict, and specify the software quality in terms of software integrity. The obtained metrics interprets the criteria influencing the implementation of software integrity. The primary goal of software integrity regarding security is ensuring the commendable and basic data around the organizations and makes it effectively achievable. In this study, we proposed two methods for finding the integrity bugs in software implementation. The first methods involve determining and consolidating the criteria of evaluation while in the second method we employed Chidamber and Kemerer Java Metrics (CKJM) to compute the software quality metrics. Furthermore, three open-source Java frameworks are utilized to analyze the effect of quality metrics on the implementation of software integrity. The proposed framework enabled to examine the most extensively employed metrics to test software integrity i.e the number of children, the coupling between objects, and response for class respectively. The empirical results suggested that the metrics calculated by the proposed framework have a significant effect on software integrity. The benefits of the proposed system to the absolute use of measurements at steady appearances of software products help in the early identification of software quality-related issues. Specific appraisal of quality levels gives better administration permeability and empowers auspicious dynamics.
Keywords:	Software Quality, Software Integrity, Correlation, ANOVA test, Quality metrics
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2020 -- Vol. 98. No. 13 -- 2020
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Title:	FINITE HORIZON MARKOV DECISION PROCESS BASED FUZZY OPTIMIZATION FOR RESOURCE ALLOCATION IN SDN ENABLED VIRTUAL NETWORKS IN IAAS CLOUD ENVIRONMENT
Author:	G. SENTHIL KUMAR , Dr.M.P. CHITRA
Abstract:	Network technologies are dealing with a massive urge to break through the fundamental endorsements of networks. Software-Defined Networking (SDN) has been leading cloud Data Centres (DC's) which states with different policy adaptation for ensuring resource management, concerning about Network Virtualization (NV) performance that is capable of finding the related hardware components to map a Virtual Machine (VM) or a virtual link which represents Virtual Network Embedding (VNE) problem. To overcome the VNE problems our work as proposed a Finite Horizon Markov Decision Process Based Fuzzy Optimization. Fuzzy inference provides an linguistic variables and set of rules to obtain best policy from the available cloud resource and predicts the execution cost for every network function virtualization. This stage also deals with uncertainities and imprecision.Based on the priority and schedulable ability the Finite Horizon Markov Decision Process dynamically allocates the resource for NFV components. Thus, our work obtains a substantial amount of energy utilization by optimizing the use of local host services and will therefore provide greater policy control for physical DCs.
Keywords:	Software- Defined Networking (SDN), Network Virtualization (NV), Virtual Machine (VM), Virtual Network Embedding (VNE), Finite Horizon Markov Decision Process, Fuzzy Optimization, Resource Allocation.
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2020 -- Vol. 98. No. 13 -- 2020
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Title:	TRAINING STRATEGY FOR A NEURAL NETWORK USING A MODIFIED GENETIC ALGORITHM
Author:	HOLMAN MONTIEL A., FREDY H. MARTÃƒÂNEZ S., EDWAR JACINTO G.
Abstract:	There are different computer models to classify groups of data, among which are neural networks, vector support machines, numerical methods, among others. However, in some cases these strategies consume a large amount of computer resources, reducing the speed of operation during their execution in the various electronic development devices. In this work, a partial solution to this limitation is proposed. The algorithm developed is a classifier that incorporates a backward-propagation neural network, which is trained by means of a modified genetic algorithm that is in charge of finding the appropriate set of weights for the neural network to classify a given group of random numbers. The proposed optimization will allow the use of this algorithm in various classification problems, not only in conventional computing units, but also on various technological platforms with reduced properties (embedded systems), maintaining an optimal balance between the use of resources and the speed of response of the device used.
Keywords:	Neural Network; Classifier; Machine Learning; Genetic Algorithms; Correlation.
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2020 -- Vol. 98. No. 13 -- 2020
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Title:	OPTIMIZATION MODEL FOR CUSTOMER BEHAVIOR WITH MARS AND KYC SYSTEM
Author:	RAHMAD SYAH, MAHYUDDIN K.M NASUTION , MARISCHA ELVENY, HENDRA ARBIE
Abstract:	Know You Customer System (KYC) is one of the technologies currently applied to control customer activities and verify accurate data for security and user satisfaction. Multivariate and dynamic growth of digital business is also the rise of payment technology in other words receiving Big Data which we must anticipate. This study, using MARS is a nonparametric method with the function of reducing and making optimal models in predicting each numerical computational structure in it. Results obtained Find a model for optimal coefficient values from large-scale data values. So that in determining decisions, as well as supporting business intelligence can be done appropriately.
Keywords:	Dynamic KYCP, Star-Up, Blockchain Technology, Business Canvas Model, MARS, Personal Financial Management.
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2020 -- Vol. 98. No. 13 -- 2020
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Title:	AN IMPLEMENTATION OF RABIN CRYPTOGRAPHY AND FIBONACCI CODES ALGORITHM IN IMAGE FILES SECURITY AND COMPRESSION
Author:	DIAN RACHMAWATI, AMALIA AMALIA, AKTUALITAS GULO
Abstract:	Image files are vulnerable to being fabricated, modified, and duplicated, which violate the copyright. Therefore, it is needed Rabin cryptography method for securing and assuring the confidentiality of the image file. Rabin cryptography algorithm is an asymmetric algorithm. The advantage of this algorithm is a simple encryption process so that it can reduce processing time, even though the used resource is limited. Encryption process in the Rabin algorithm causes enlargement of the data size, moreover, the capacity of the image file that tends to be large, it can cause to the slowing down of the information exchange process. So it is needed Fibonacci codes method to reduce or compress the data size. Fibonacci codes is a compression algorithm that uses an array of the Fibonacci integer to code the bit value from the data or file which compressed. In this research, the writer combines the Rabin cryptography algorithm for securing image files and Fibonacci codes for compressing data. This research will be done in two schemes test. The first scheme which will be done that the image file is encrypted first with Rabin cryptography algorithm, then the result of encryption is compressed with the algorithm of the Fibonacci code. And the second scheme which will be done that image file is compressed first with Fibonacci codes, then the result of the compression is encrypted with the Rabin cryptography algorithm. Image file to be tested with extension are .JPG, .PNG, .BMP. System implementation uses C# programming language. The result of this research shows that the Rabin cryptography method can secure originality and confidentiality of data with the first scheme and the second scheme, whereas the Fibonacci codes method is ineffectively to reduce data size with extension .JPG and .PNG in the second scheme. Fibonacci codes method produce RC (Ratio Compression), CR (Compression of Ratio), and SS (Space Saving) with each values are 0.89, 115,52%, -15,53% in average. While in file with BMP extension Fibonacci codes method can be used effectively to reduce the data size, where this method Rc = 1,4364, Cr = 70,98%, and SS = 27,47 % in average.
Keywords:	Fibonacci codes, Rabin, Cryptography, Compression
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2020 -- Vol. 98. No. 13 -- 2020
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Title:	ADAPTIVE CLASSIFICATION IN DATA STREAM MINING
Author:	MOSTAFA M. YACOUB , AMIRA REZK , M. B. SENOUSY
Abstract:	Data streams gained obvious attention by researches for years. Mining this type of data generates challenges because of their special nature. Classification is one of the major approaches of Data Stream Mining (DSM). Concept drift (changes in pattern of data over time) is one of the major challenges that is needed to be adapted in data streams. Another challenge is high dimensional data streams. This paper provides a review for classification techniques in adaptive data stream mining. Focusing on both challenges; concept drifts and dimensionality reduction and dividing these techniques into incremental and ensemble. Incremental classifiers such as Very Fast Decision Trees (VFDT) and Concept-adapting Very Fast Decision Trees (CVFDT) were tested. Adaptive Random Forests (ARF) was taken as an example for adaptive ensemble classifiers. Furthermore, a practical analysis between VFDT, CVFDT and ARF was held. The analysis was according to accuracy, processing speed, and tree size. Accuracy did not vary much between the three algorithms. ARF has much better results in speed and has the smallest number of tree nodes.
Keywords:	Data Stream Mining, Classification, Decision Trees, Adaptivity, Concept Drift
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2020 -- Vol. 98. No. 13 -- 2020
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Title:	LOCAL NAVIGATION MAP PROCESSING ALGORITHM TO IDENTIFY INDOOR OBJECTS AND GENERATE MOTION TRAJECTORY FOR ANTHROPOMORPHIC ROBOT
Author:	YANA KOSTELEY, DMITRY ZHDANOV, ARTEM BUREEV, LIUDMILA KHOKHLOVA
Abstract:	The article describes an approach to the analysis of a local indoor navigation map derived from a lidar point cloud represented as a projection on a horizontal plane. The article analyzes the applicability of the graph theory and binary image processing methods for structuring and uniting the elements of a noisy and segmental local navigation map layout. On an initial map layout (walls, free space and internal environment objects), stand-alone interior elements are detected, and the points of wall borders are filtered and closed up. Mathematical morphology methods and shortest path and connected component separation algorithms are used to complete these tasks. The authors have developed a trajectory generation algorithm consisting of several turning and straight-line motion commands.
Keywords:	Local Navigation Map, Mathematical Morphology, Flood Fill, Lee Algorithm, Connected Component Separation
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2020 -- Vol. 98. No. 13 -- 2020
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Title:	THE SOLUTION TO THE PROBLEM OF PROCESSING BIG DATA USING THE EXAMPLE OF ASSESSING THE SOLVENCY OF BORROWERS
Author:	GULNAR BALAKAYEVA, DAUREN DARKENBAYEV
Abstract:	This article provides a literature review and comparative analysis of methods for solving the problem of building a credit scoring model; gives definitions of the concepts of large volumes of data (Big Data); and provides an overview of existing tools for processing and storing large volumes of data. The main problems and tasks of building credit scoring are identified. The general statement of the problem is presented. Analysis of the actual problems of assessing bank credit risk, and predicting the credit worthiness of the borrower, etc. is given. The mathematical model of mortgage lending based on the processing of large amounts of data is studied. This article discusses various technologies, including forecasting using modern technologies. This contributes to the storage of big data, as well as the passage of a parallel process. We consider the problems that arise when working with big data, and identify the need for further research, to include the use of big data processing methods for real business processes in organizations that are faced with the need to process large amounts of data. In addition, further analysis of the problems associated with modeling the processing of big data is identified.
Keywords:	Big Data, NoSQL, Database, Map Reduce, Hadoop, Model, Scoring Technology
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2020 -- Vol. 98. No. 13 -- 2020
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Title:	GRAYSCALE IMAGE ENHANCEMENT FOR ENHANCING FEATURES DETECTION IN MARKER-LESS AUGMENTED REALITY TECHNOLOGY
Author:	DEVI WILLIEAM ANGGARA, MOHD SHAFRY MOHD RAHIM, AJUNE WANIS ISMAIL, RUNIK MACHFIROH, ARIF BUDIMAN, ARIS RAHMANSYAH, DAHLIYUSMANTO, NOOR AZEAN ATAN
Abstract:	Tracking is a fundamental task in Augmented Reality (AR) technology which requires robust real-time to properly adjust real and virtual objects in a single alignment, so that, both objects appear to coexist in the same world. Marker-less tracking has been explored to overcome the limitations of conventional marker-based tracking in AR. By capturing real surroundings to produce the features, the marker-less tracking will recognize these features to overlay the virtual objects on the top of the captured features. The features have been tracked in real-time by the display device, based on the real environment. Therefore, this article aimed to explain the features detection using Features Accelerated Segment Test (FAST) to detect corner features. Related works were reviewed and the features extraction for AR framework using Grayscale Image Generation (GIG) were presented. In addition, to enhance details of grayscale images, a comprehensive study was performed on the three techniques of Contrast Enhancement (CE), namely, Colormap, HE and CLAHE to determine the best method for robust features detection. The findings showed Colormap to be the best technique, compared to HE and CLAHE, in terms of noise, the accuracy of the corner, distributed histogram and amount of features.
Keywords:	Augmented Reality, Contrast Enhancement, Template Matching, FAST Corner Detector, GIG
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2020 -- Vol. 98. No. 13 -- 2020
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