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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
October 2018 | Vol. 96 No.20

Title:	FACTORS AFFECTING IS SUCCESS AND TECHNOLOGY ACCEPTANCE: A CASE STUDY
Author:	SUTJAHYO, SILVI HARUN, KEYIE PRIARTI, MARIA GORETHI RUTH YULITA, MAUREEN MOLITA, JAROT S. SUROSO
Abstract:	Today, Information technology is the concern of corporate executives, and a challenge in ensuring alignment between the functions of information systems and business. PT. XYZ is one of the insurance company in Indonesia that has implemented the core information system for operational, however, the fact is that the number of complaints against the system, and the reluctance to use the system continues to increase. This study will evaluate the core operational information system in PT. XYZ using IS success model Delone McLean and technology acceptance model in evaluating factors influencing IS success and technology acceptance and determining factors that still need to be improved in achieving IS success and technology acceptance to company information system that has been implemented. The number of samples is 194 respondents, and all of them are employees of PT. XYZ that uses the core information system. Data obtained from questionnaires distributed to respondents and measurement of validity, reliability and regression analysis using SPSS 20. Found that the most important factor of IS success and technology acceptance is information quality.
Keywords:	Core Information System, Application, Technology Acceptance, IS Success, Insurance Company
Source:	Journal of Theoretical and Applied Information Technology 30^st October 2018 -- Vol. 96. No. 20 -- 2018
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Title:	A MULTI-AGENT ARCHITECTURE FOR EVACUATING PILGRIMS IN PANIC AND EMERGENCY SITUATIONS: THE HAJJ SCENARIO
Author:	ABDALLAH NAMOUN, AABID MIR, AHMAD B. ALKHODRE, ALI TUFAIL, AHMED ALREHAILI, MOHAMMAD FARQUAD, MAJID ALWAQDANI, TURKI ALGHAMDI, MOHAMED BENAIDA
Abstract:	This paper proposes and presents the details of an agent-based architecture that has the capacity to model, simulate the movement of, and guide crowds with panic behavior in highly-dense areas in the events of man-made and natural threats. The most populated human gathering in the world, the Muslim pilgrimage event (also known as Hajj) which attracts more than two million people in six days is chosen to guide the identification of the requirements and main concepts of the agent simulation. The inferred requirements are used to guide the selection of an appropriate simulation tool following an extensive survey of potential simulation tools. The architecture uses software agents to represent groups of people along with their real time characteristics such as density, movements and panic levels, collected from various data sources. Support vector machine is combined with the fuzzy logic theory to predict pilgrims' behaviors and movements in case of panic situations. Initial simulation tests and results of the SVM model demonstrated that it is feasible to minimise the problem of modelling large crowds by selecting the best representative crowds that best reflect pilgrims’ behaviors. Furthermore, the implications of this architecture and a future plan are presented.
Keywords:	Multi-agent Architecture, Crowd Modeling and Simulation, Crowd Management, Support Vector Machine, Fuzzy Set Theory, Behavior Prediction.
Source:	Journal of Theoretical and Applied Information Technology 30^st October 2018 -- Vol. 96. No. 20 -- 2018
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Title:	NEURAL NETWORK BASED APPROACH FOR IMPROVING COMBINATORIAL COVERAGE IN COMBINATORIAL TESTING APPROACH
Author:	RAMGOUDA PATIL, V CHANDRA PRAKASH
Abstract:	Recent advancements in technology has shown significant impact on social life, where computers have attracted huge attention due to its importance in socio-economic progress. Due to the growth in various computer technologies, software-based application has played pivotal role in the social and economic development. However, poor quality of software module may cause industrial loss; hence software quality improvement remains an attractive research field. Several techniques have been presented for improving the software quality by developing software testing methods. In this field of software testing, combinatorial testing is considered as the most promising scheme for improving software testing and quality improvement by reducing the number of test cases. This combinatorial testing strategy can help to provide a better solution for given software product. In this work, we have focused on software testing using combinatorial testing with the help of IPOG approach which is used for test case generation of the 2-way test scenario. Later, neural network scheme is incorporated for test case generation which provides most suitable test scenario for combinatorial coverage. For given software product, if random testing is performed and its test cases are available, then for this software we can easily identify how much combinatorial coverage is already performed, and how many new test cases are to be added to those available test cases of random testing so that appropriate testing coverage is achieved. A comparative scheme is presented which shows that proposed approach gives the best solution for test case generation for software testing.
Keywords:	Combinatorial Testing, Neural Network, IPOG, Software Testing, Test Case Generation, combinatorial coverage
Source:	Journal of Theoretical and Applied Information Technology 30^st October 2018 -- Vol. 96. No. 20 -- 2018
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Title:	MARKOV-MODULATED BERNOULLI DYNAMIC GENTLE RANDOM EARLY DETECTION
Author:	MAHMOUD BAKLIZI, JAFAR ABABNEH, MOSLEH M. ABUALHAJ, NIBRAS ABDULLAH, ROSNI ABDULLAH
Abstract:	This paper proposes an efficient modeling of the Dynamic (DGRED) algorithm using a three state Markov Modulated Bernoulli arrival process (MMBP-3) for primary period congestion detection at the router buffer. The purpose of using Markov is two folds, the first is to implement DGRED with multiple traffic classes, where in each class may have different priorities and the second is to enhance the mechanism of DGRED in stabilizing the average queue length (aql) between the allocated threshold values of minthreshold and maxthreshold, using variable calculating parameters, which is stored in the utilized states of Markov. The (MMBP-3) is employed to replace the conservative and widely used Bernoulli process (BP) in assessing DGRED method. Accordingly, a three dimensional discrete time Markov chain is provided to implement DGRED algorithm for three traffic classes where each dimension corresponds to a traffic class with its own parameters. The (MMBP-3) is deal with correlation and burstiness in the network traffic. The developed algorithm allows for faster response to the changes in the network, congestion-to-non-congestion and non-congestion-to-congestion, which lead to decrease packet losses and improvement of network performance. The proposed method is evaluated in comparison to the DGRED and other AQM methods, the results reveal that the proposed algorithm provides better performance compared to DGRED, RED, GRED, and Adaptive GRED in relations of delay packet loss, delay and mean queue length. The most appropriate arrival process for DGRED method is IBP for D, mql, PL, and DP while congestion occurs. Though, this process cannot discourse correlation. Thus MMBP-3 is the greatest choice as it detects both correlation and bursty things.
Keywords:	Congestion Control, Adaptive GRED, (RED), Performance Evaluation, MMBP-3, Simulation.
Source:	Journal of Theoretical and Applied Information Technology 30^st October 2018 -- Vol. 96. No. 20 -- 2018
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Title:	DISTANCE-SCORE COMBINED MODEL IN AUTOMATIC HIGH SCHOOL STUDENT ENROLLMENT SYSTEM
Author:	PURBA DARU KUSUMA
Abstract:	There are some problems in the existing high school student enrollment system in Indonesia. Besides its main goal to create equality in education and student distribution, there are protests from people, especially parents. The new zoning system is blamed because it neglects student national exam score so that there is not any incentive to become smart student. As far as his house is near to the school, student with low national exam score is still prioritized. This policy triggers many families to create fake family certificate. The other policy in accommodating low economy student is also blamed in triggering lots of fake poor family certificate. Based on these real problems, in this paper, we propose new automatic high school student enrollment system. In this work, both home-to-school distance and national exam score are accommodated so that the student is allocated the school that its location is as near as possible from his house. Meanwhile, there is incentive for student who has high national exam score. In this work, we propose four high school student enrollment models. The first model is full round robin total score based model. The second model is semi round robin total score based model. The third model is exam score prioritized-clustered school combined model. The fourth model is exam score prioritized-semi zoning model. These four proposed models then are tested and are compared with the existing models. There are several research findings in this research. The first model produces the best equality in distributing students so that smart students are not concentrated in high quality schools group only. Meanwhile, the first model also produces the lowest home-to-school distance. The second model produces gap among schools with different quality level. By using this model, higher quality schools get benefits in receiving lower average home-to-school distance and students with higher average national exam score. The third model produces significant gap in average national exam score accepted students. Meanwhile, the average home-to-school distance is tended to be higher than the first and second proposed models. The fourth model produces equality in distributing students based on their national exam score when the maximum distance is set moderate. In all models, the number of students does not affect the result.
Keywords:	High School Student Enrollment, National Exam Score, Nearest Distance, Zoning System, Round Robin.
Source:	Journal of Theoretical and Applied Information Technology 30^st October 2018 -- Vol. 96. No. 20 -- 2018
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Title:	BOUNDARY VALUE PROBLEMS FOR DIFFERENTIAL EQUATIONS BY USING LIE GROUP
Author:	EMAN ALI HUSSAIN, ZAINAB MOHAMMED ALWAN
Abstract:	In this task, we applied Lie group method for solving boundary value problems (BVPs) of partial differential equations (PDEs) to obtained the fundamental solutions .
Keywords:	Lie group, Invariance ,BVPs, Exact Solution, Boundary Condition
Source:	Journal of Theoretical and Applied Information Technology 30^st October 2018 -- Vol. 96. No. 20 -- 2018
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Title:	SENTIMENT ANALYSIS REVIEW ON TWITTER ABOUT THE SUPREME COURT REPUBLIC OF INDONESIA USING SUPPORT VECTOR MACHINE ALGORITHM BASED PARTICLE SWARM OPTIMIZATION AS FEATURE SELECTION METHODS
Author:	ASTRIA YUMALIA, MUKHNERI MUKHTAR, MOCHAMAD WAHYUDI, DWI ANDINI PUTRI, SIGIT SWASONO, DWI ASTUTI RATRININGSIH
Abstract:	The Supreme Court of the Republic of Indonesia has sought to develop a positive image of the judiciary through various programs. Sentiment analysis constituted a popular research area even in sentiment analysis of text content on twitter. The Support Vector Machine (SVM) classification algorithm was proposed by many researchers to be used in the review sentiment analysis. SVM is able to identify the separated hyperplane that maximizes the margin between two different classes. However, SVM has a weakness for parameter selection or suitable feature. Feature selection can be used to reduce the less relevant attributes on the dataset. The feature selection algorithm used is Particle Swarm Optimization (PSO) to solve the optimization problem in order to increase the classifications accuracy Support Vector Machine. This research generate text classification in the positive or negative of The Supreme Court of the Republic of Indonesia review on twitter. The evaluation was done by using 10-Fold Cross Validation and the measurement accuracy is measured by Confusion Matrix and ROC curve. The result showed an increasing in accuracy SVM of 91.05% to 91.72%.
Keywords:	Sentiment Analysis, Twitter, SVM, PSO, Feature Selection, Classification Text.
Source:	Journal of Theoretical and Applied Information Technology 30^st October 2018 -- Vol. 96. No. 20 -- 2018
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Title:	GRAPH MANAGEMENT SYSTEMS: A SURVEY (REVIEW PAPER)
Author:	MAURIZIO NOLE, CARLO SARTIANI
Abstract:	In the recent years many real-world applications have been modeled by graph structures (e.g., social networks, mobile phone networks, web graphs, etc.), and many systems have been developed to manage, query, and analyze these datasets; to cope with the ever-increasing size of graph datasets, most of them adopted a distributed approach. These systems could be divided into specialized graph database systems and large-scale graph analytics systems. The first ones consider end-to-end data management issues including storage representations, transactions, and query languages, whereas the second ones focus on processing specific tasks over large data graphs. In this paper we provide an overview of several graph database systems and graph processing systems, with the aim of assisting the reader in identifying the best-suited solution for her application scenario.
Keywords:	Big Data, Graph Data Management, Graph Processing Systems, Semistructured Data, Data Analytics
Source:	Journal of Theoretical and Applied Information Technology 30^st October 2018 -- Vol. 96. No. 20 -- 2018
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Title:	A SCALABLE SERVICE ALLOCATION NEGOTIATION FOR CLOUD COMPUTING
Author:	LESZEK SLIWKO
Abstract:	This paper presents a detailed design of a decentralised agent-based scheduler, which can be used to manage workloads within the computing cells of a Cloud system. This scheme in based on the concept of service allocation negotiation, whereby all system nodes communicate between themselves and scheduling logic is decentralised. The architecture presented has been implemented, with multiple simulations run using real-word workload traces from the Google Cluster Data project. The results were then compared to the scheduling patterns of Google’s Borg system.
Keywords:	Distributed Scheduling; Agents; Load Balancing; MASB
Source:	Journal of Theoretical and Applied Information Technology 30^st October 2018 -- Vol. 96. No. 20 -- 2018
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Title:	A NEW E-COMMERCE MODEL OF C2M BASED ON B2C: FOCUS ON BIYAO CASE
Author:	JING CHEN, MYUNGKEUN JEE, JONGCHANG AHN
Abstract:	C2M (consumer to manufacturer) is a new kind of Internet e-commerce model. This study analyses the BIYAO mall, which is a representative platform of C2M. This study investigates the macro developing environment of BIYAO by the aid of the PEST analysis method, the result indicates that BIYAO is basically conducive to the development of a social environment, and the support of laws and regulations, and information technology, which are the powerful backbone of BIYAO. In addition, the consumers’ changing consumption ideas are the strong driving force of BIYAO. The study surveys the development situation of BIYAO by means of the SWOT analysis approach. The findings are that BIYAO should eliminate the potential threat which may occur in its development process with the help of their team work’s rich experience and favorable environment. BIYAO will provide consumers with "high quality and low price" goods and services with the principle of strict investment promotion and the principle of "removing the intermediate circulation". BIYAO has developed a strict transaction process, return process and customer complaints process, the greatest extent to provide pre-sales and after-sales service facilities for consumers. In addition, the study points out the developing advantages of BIYAO, and proposes a solution to the C2M. Finally, the advantages and disadvantages between C2M and F2C (factory to consumer) are compared.
Keywords:	C2M (consumer to manufacturer), BIYAO case, E-commerce, B2C (business to consumer), F2C (factory to consumer), Case study
Source:	Journal of Theoretical and Applied Information Technology 30^st October 2018 -- Vol. 96. No. 20 -- 2018
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Title:	IMPACT OF E-SERVICE ON CUSTOMER LOYALTY IN MARKETPLACE IN INDONESIA
Author:	SFENRIANTO, IVAN OLIVER, ARIO CHRISTIANO, MEIDINA PUTRI MULANI
Abstract:	Online sales in Indonesia have experienced tremendous growth every year. With traditional class economic growth, e-marketplace has become the most promising online online business in Indonesia. There are five e-marketplaces that are the most popular in Indonesia, such as: Tokopedia, Lazada, Shopee, Elevania and Bukalapak, which have quite a lot of customers. But the issue of e-service is a major concern to increase the loyalty of costomers for e-marketplace in Indonesia. The purpose of this journal is to study what factors can affect e-service to customer loyalty in transacting in Indonesia's e-marketplace. You can help sellers who do business in e-marketplace in order to better understand the things that need to be improved in their services, in order to gain loyalty from their customers. Data collected by 107 respondents using e-marketplace. The results showed that usability perception factors had a significant effect on e-service, and e-service had a significant effect on customer loyalty. Trust and perceived ease of use are not felt for e-service. It can be concluded that e-marketplace is a new thing in Indonesia and there is a complex business environment to get customer loyalty.
Keywords:	E-Marketplace, E-Service, Loyality, Online Business.
Source:	Journal of Theoretical and Applied Information Technology 30^st October 2018 -- Vol. 96. No. 20 -- 2018
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Title:	FAST SELECTIVE ENCRYPTION FOR VIDEO STREAM OF HIGH EFFICIENCY VIDEO CODING STANDARD
Author:	MOHAMMED A. SALEH, NOORITAWATI MD. TAHIR, AND HABIBAH HASHIM
Abstract:	In this paper, a lightweight encryption method is developed to protect the visual information of video. Due to the new video coding standards High Efficiency Video Coding (HEVC), and in order to meet the compression requirements a new enhancement for the existing encryption schemes is needed. This is because the lack of the ability of the current encryption methods to balance the security level with the compression efficiency of HEVC standard. Hence, we utilized the selective encryption for the sensitive syntax elements to secure video transmission and fulfill the attributes of HEVC standard. This is done via selection of sensitive syntax elements (Absolute Coefficient Levels) that are encrypted using Advanced Encryption Standard (AES) algorithm. On several video benchmarks, the analysis results obtained that the relevant security level of visual video perception is achieved, a trade-off between encryption reliability, flexibility, maintaining the HEVC bitstream format compliance, and computational complexity are provided. The protection level of this method is strong enough against plaintext and brute force attacks.
Keywords:	HEVC/H.265, selective encryption, video security, AES, bin string encryption.
Source:	Journal of Theoretical and Applied Information Technology 30^st October 2018 -- Vol. 96. No. 20 -- 2018
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Title:	AN EFFICIENT IMPROVEMENT OF FRAME AGGREGATION MECHANISMS FOR VHT AT MAC AND PHY LAYERS IN IEEE802.11AC USING MIMO CHANNEL
Author:	ALI M. ALSAHLANY , DHURGHAM ABDULRIDHA JAWAD AL-KHAFFAF
Abstract:	This paper presents and investigates the amendments of WLAN on physical and MAC layers, which can help the IEEE802.11ac to achieve the maximum data rate. The analytical model has been driven the normalized throughput. This work has discussed three aggregation techniques such as Aggregate MAC Protocol Data Unit (AMSDU), Aggregate MAC Service Data Unit (AMPDU), and the proposed combining technique of AMSDU and AMPDU is analyzed and illustrated. Our simulation model consider many technologies such as the modulation, coding, channel bounding, and spatial streams. The best results have been achieved with the hybrid technique of AMSDU/AMPDU in terms of MAC efficiency and the throughput. In case of QPSK with 40 MHz and 4-Spatial Streams (4-SSs), the highest improvement is recorded for AMSDU/AMPDU with increasing the throughput by 11.5 Mbps and improving the MAC efficiency around 14.38% compared with conventional aggregation techniques.
Keywords:	Frame aggregation, IEEE 802.11ac, MAC layer, Throughput, AMSDU and AMPDU.
Source:	Journal of Theoretical and Applied Information Technology 30^st October 2018 -- Vol. 96. No. 20 -- 2018
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Title:	HYBRID JAMES-STEIN AND SUCCESSIVE DIFFERENCE COVARIANCE MATRIX ESTIMATORS BASED HOTELLING’S T2 CHART FOR NETWORK ANOMALY DETECTION USING BOOTSTRAP
Author:	MUHAMMAD AHSAN, MUHAMMAD MASHURI, HIDAYATUL KHUSNA
Abstract:	Statistical process control (SPC) is one of the powerful statistical methods that continuously improves the manufacturing process. The advantage of using the method in network anomaly detection is the technique does not need the knowledge of an information from the previous intrusions. The Hotelling's T2 is the mostly used control chart for network intrusion detection. However, Hotelling's T2 chart, which uses the conventional mean and covariance matrix, is sensitive to the outlier presence. Therefore, the conventional method is not effective to be implemented in Intrusion Detection System. To overcome this problem, Successive Difference Covariance Matrix (SDCM), which is one of the robust covariance matrix estimators, can be implemented in estimating the covariance matrix. Meanwhile, the James-Stein estimator can be adopted in estimating the mean vector of the Hotelling’s T2 control chart. The utilization of the bootstrap resampling method is intended to obtain the more accurate control limit of the proposed chart. The combination of these estimators with the bootstrap resampling approach demonstrates the better performance when it is used to monitor the anomaly in the network than the other control limit approaches in training and testing dataset. In addition, the IDS based on the proposed chart has better performance than the other existing charts based on its hit rate and FN rate criteria. The proposed method also outperforms some classifier methods.
Keywords:	T2 control chart, james-stein, successive difference covariance matrix, bootstrap, network anomaly detection
Source:	Journal of Theoretical and Applied Information Technology 30^st October 2018 -- Vol. 96. No. 20 -- 2018
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Title:	MODELING OF STOCK MANAGEMENT BY PARAMETRIC MODELS ARX, ARMAX, BJ AND OE
Author:	HICHAM FOURAIJI, BANAYAD NSIRI, BAHLOUL BENSASSI
Abstract:	In this paper, we propose a new approach to the modeling of storage systems. This method is based on the knowledge of the automatic domain, in order to construct a mathematical model that accurately formalizes the behavior of the system studied. The approach adopted for this study is the parametric identification of ARX, ARMAX, Box Jenkins and OE linear systems. The logistic system studied will be considered as a black box, which means that the input and output data of the system will be used to identify internal system parameters and propose a mathematical model.
Keywords:	Warehousing system, Modeling, Identification, ARX, ARMAX, OE, BJ
Source:	Journal of Theoretical and Applied Information Technology 30^st October 2018 -- Vol. 96. No. 20 -- 2018
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Title:	ANDROID MALWARE CLASSIFICATION BASE ON APPLICATION CATEGORY USING STATIC CODE ANALYSIS
Author:	AZMI AMINORDIN1, FAIZAL M. A. , ROBIAH YUSOF
Abstract:	The great shipment of Android mobile devices throughout the world has surged the application develop-ment. Indirectly, this scenario had invited the malware creator to be in-line with the technology evolution. One of the threats is the leakage of privacy data and it is a serious subject. To overcome this, the Android application usually being examine through static or dynamic analysis. In static analysis approach, re-searcher commonly considered combination static features to identify the benign and malicious applica-tion. This paper presents a proof of concept on classifying Android benign and malicious apps by its appli-cation category. At the same time, this paper proposes a new framework for malicious detection focusing on the leakage of user privacy using minimum number of the request permissions and API calls features. Several machine learning classifiers with several training and testing percentage applied in this study to compare the accuracy. The result show that, applications in same category reported more accurate per-formance in identify malicious apps compared to non-category based. By applying features ranking and information gain features selection, Random forest classifier with 10 folds cross validation for both “Book and Reference” and “Personalization” category achieved higher true positive rate also lower false positive rate.
Keywords:	Android, Category-Based, Static, Machine Learning
Source:	Journal of Theoretical and Applied Information Technology 30^st October 2018 -- Vol. 96. No. 20 -- 2018
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Title:	ADOPTION OF E-LEARNING SYSTEMS IN TANZANIAS UNIVERSITIES: A VALIDATED MULTI FACTORS INSTRUCTORS MODEL
Author:	DEOGRATIUS MATHEW LASHAYO, MOHAMMED HAZIM ALKAWAZ, MD GAPAR MD JOHAR
Abstract:	Current studies indicate that there is no comprehensive instructor model in e-learning systems’ adoption in universities in Tanzania. This paper addresses this problem by developing an instructor model through adapting DeLone and McLean (2003) information system success model. The developed research model answers the following debatable questions: (1) what are the factors which affect the adoption of e-learning systems’ in universities in Tanzania? (2) what is the model which systematically affect adoption of e-Learning systems’ in Tanzania? (3) How can this proposed model be validated? This research study employs quantitative, cross-sectional survey, designed for a total of 86 instructors in eight universities in Tanzania. The data is analysed using the Structural Equation Modelling (SEM) using Analysis of Moment of Structure (AMOS 21 software). The results show that the predictors of adoption of e-learning systems in universities include: (1) Service Quality (SQ), (2) Technical Service Quality (TSQ), (3) Course Quality (CQ), (4) Intention to Use (ITU), (5) E-Learning Actual Use (EAU), and (6) Instructor Satisfaction (IS). These findings will help universities, government, e-learning institutions and other e-learning stakeholders to develop suitable policies and strategies to boost sustainability of e-learning systems, as well as acting as the tool to developers in the course of e-learning systems’ adoption. This valid and reliable model bridges the gap of literatures particular in e-learning systems’ adoption in universities in Tanzania and developing world at large. The novelty of this paper lies on impact of trust, university readiness environmental factors, intention to use and actual use on IS success model based on instructor’s perceptions in Tanzania.
Keywords:	E-learning systems, Adoption, Universities, Tanzania, Multi-Factors, DeLone and McLean (2003) IS model, Instructor.
Source:	Journal of Theoretical and Applied Information Technology 30^st October 2018 -- Vol. 96. No. 20 -- 2018
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Title:	PREDICTING PERSONALITY TRAITS OF FACEBOOK USERS USING TEXT MINING
Author:	REINERT YOSUA RUMAGIT, ABBA SUGANDA GIRSANG
Abstract:	Currently, social media is used to express the users’ opinion, perception and so on. Status created by social media users describes the characteristics of their personality. This research was conducted to find out the traits of social media users on Facebook by mining the users’ Facebook posts. The texts were categorized and classified using SVM, Naïve Bayes and Logistic Regression in order to get the traits of each user. The data for this case study was taken from Indonesian users of Facebook. The result of this mining was compared to the results of the previous research. To handle the problem of imbalanced user data, synthetic minority over-sampling technique (SMOTE) was used. The results of this study indicated that the results generated using the proposed method successfully outperformed the results of the previous research with an average accuracy of 89.08%.
Keywords:	Text Mining, Personality Prediction, SMOTE, SVM, Naïve Bayes, Logistic Regression
Source:	Journal of Theoretical and Applied Information Technology 30^st October 2018 -- Vol. 96. No. 20 -- 2018
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Title:	CSV2RDF: GENERATING RDF DATA FROM CSV FILE USING SEMANTIC WEB TECHNOLOGIES
Author:	S M HASAN MAHMUD, MD ALTAB HOSSIN, 5HOSNEY JAHAN, SHEAK RASHED HAIDER NOORI, MD. FOKHRAY HOSSAIN
Abstract:	Recently, a large amount of Governments and public administrations data are stored on the Web in various file formats, mostly in the tabular data form such as Comma Separated Values (CSV) or Excel. CSV format is simple and practical, but it is difficult to express the relevant metadata such as data provenance, meaning of data fields, relationships between data fields, and user access approaches/rights, etc. In order to make the CSV data semantically structured, interoperable, accessible and reusable for various Web applications, they need to be extracted from the CSV files and converted into the Resource Description Framework (RDF) format that provides superior data assimilation and query functionality. In this paper, we focus on how the Semantic Web technologies are used to convert CSV data into RDF. Therefore, we present a method and techniques to parse the CSV file; the parsed CSV data are complemented with metadata annotations to generate the annotated tabular data model which is then converted into RDF triples. According to the conceptual correspondences between the CSV data model and RDF data model, we designed a set of algorithms to generate RDF triples from the CSV data. Our developed prototype tool, CSV2RDF, is used for evaluating the performance of the proposed method through real-world CSV datasets. The implementation and experimental outcomes demonstrate that our pro-posed method is feasible to generate RDF data from CSV datasets, with satisfactory performance on any size of data sets.
Keywords:	Comma Separated Values (CSV), Resource Description Framework (RDF), Annotated Tables, CSV to RDF Conversion, Metadata, Semantic Web.
Source:	Journal of Theoretical and Applied Information Technology 30^st October 2018 -- Vol. 96. No. 20 -- 2018
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Title:	SIBER-DELTAKE: AN IMPROVED ACO-KM-ECC BASED TRUST AWARE ROUTING TECHNIQUE IN WSN WITH OPTIMAL DATA RESOLUTION
Author:	V. NEELIMA, A. R. NASEER, G. NARSIMHA
Abstract:	In this paper, our proposed Hybrid model SIBER-DELTAKE, an improved ACO-KM-ECC trust aware routing protocol is presented to provide secure routing in Wireless Sensor Networks by tackling both the identity and behavior related attacks launched by malicious nodes. The proposed SIBER-DELTAKE protocol is built on Ant Colony Optimization (ACO) which employs K-Medoids(KM) algorithm for formation of clusters and setting up of cluster heads to achieve optimal data resolution. It uses Elliptical Curve Cryptography (ECC) mechanism with key generation and management to secure data integrity as well as data privacy thereby establishing secure routing. It further takes into account Distance, Energy, Link Quality, Trust-Awareness metrics in the routing decision to provide trust enabled routing to prevent non-forwarding attacks by insider misbehaving nodes. The performance evaluation of our proposed hybrid model SIBER-DELTAKE was carried-out using NS-2 Simulator for varying network sizes. Our simulation results indicate that SIBER-DELTAKE performs extremely well in terms of malicious node mitigation, delivering of packets, delay in transferring packets, energy consumption and throughput thereby demonstrating the model effectiveness.
Keywords:	Wireless Sensor Networks, Ant Colony Optimization, Secure Routing, Trust Aware Routing, K-Medoids Clustering Algorithm, Elliptic Curve Cryptography, Energy Balancing, Network life Maximization, Swarm Intelligence
Source:	Journal of Theoretical and Applied Information Technology 30^st October 2018 -- Vol. 96. No. 20 -- 2018
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Title:	CONTRAST ENHANCEMENT FOR MULTI-MODALITY IMAGE FUSION IN SPATIAL DOMAIN
Author:	NADA JASIM HABEEB, ALI AL-TAEI, MOHAMMED FADHIL-IBRAHIM
Abstract:	In some scenes that cover a large area, some of the cameras capture images that may be affected by weather conditions or illumination changes, this causes the exposure of these images to a lack of focus, blur, or/and noise. Multi-model image fusion is a significant technique in computer vision and image processing to solve these problems. In this paper, a multi-model image fusion is proposed and presented in three case studies. Each case has a different scheme and all cases have the same goal. The goal of the proposed algorithm is to enhance the source images in spatial domain before fusion process leading to increase the quality of fused image. The techniques, which are used in the proposed method, are Principle Component Analysis, Histogram Equalization; sharpen filter, and Weighted Averaging fusion. Comparison analysis is achieved using some focus measurements to test the performance of the proposed algorithm in the three cases comparing with the baseline fusion techniques. The experimental results showed that the proposed method obtains better performance in preserving gradation contrast and enhancing fused image quality.
Keywords:	Multi-model image fusion, Histogram Equalization, sharpen filter, Principle Component Analysis, Weighted Averaging fusion, focus metrics
Source:	Journal of Theoretical and Applied Information Technology 30^st October 2018 -- Vol. 96. No. 20 -- 2018
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Title:	CLOUD COMPUTING INVESTIGATION FOR CLOUD COMPUTER NETWORKS USING CLOUDANALYST
Author:	YAQEEN SABAH MEZAAL, HADI HUSSEIN MADHI, THULFIQAR ABD, SHAHAD KHALID KHALEEL
Abstract:	In this paper, the performances of load balancing algorithms; Round Robin, Equally Spread Current Execution, and Throttled, in two workload cases, normal and burst are investigated using CloudAnalyst simulator tool. The main objective is to examine the effect of three experiments for regular and irregular normal workloads on the performance of different load balancing algorithms as well as for bursty workload. Each test has two different configurations for parametric investigations. These parametric studies can be used to analyze any electronic service provided by cloud technology vendors in any institutions, especially those offer self-reporting details for every day.
Keywords:	Cloud Computing, Cloudanalyst, Load Balancing Algorithms.
Source:	Journal of Theoretical and Applied Information Technology 30^st October 2018 -- Vol. 96. No. 20 -- 2018
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Title:	ASSESSING ROLE MINING ALGORITHMS USING RMINER TOOL IN IDENTIFYING THE BEST MODEL FOR ACCESS CONTROL
Author:	NAZIRAH ABD HAMID, ALA ALAROOD, AZIZAH ABDUL MANAF, RABIAH AHMAD
Abstract:	Role-based access control model has been accepted by many organizations because of the security feature that the model offers. Generally, role-based access control executes based on a role which includes set of permissions that built in a matrix form and the advantage of this model is the flexibility to modify or reassign the roles of a user if the permissions are changed. However, one of the main challenges in designing and executing the role-based access control model is to define a complete and correct set of roles and assigning them with permissions and therefore to solve this problem, the researchers have proposed role mining algorithms to produce such role set. Moreover, there are only a few comprehensive studies have been carried out to compare these algorithms and the evaluations are usually using different dataset and evaluation criteria. In order to give the researcher some insights into their performances, this paper presents an analysis on some of the well-known role mining algorithms by using RMiner tool that can be applied for role mining process and deliberate some of the dataset that can be used in role mining environment.
Keywords:	Access Control, RBAC, Review, Role Mining, Trends
Source:	Journal of Theoretical and Applied Information Technology 30^st October 2018 -- Vol. 96. No. 20 -- 2018
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Title:	PROPOSING A NEW TECHNICAL QUALITY REQUIREMENTS FRAMEWORK FOR MOBILE LEARNING APPLICATIONS
Author:	DR. MOHAMMED AMIN ALMAIAH , DR. ALAMRI, MAHDI MOHAMMED
Abstract:	Most of mobile learning applications might fail and not effectively used just because of bad selection of appropriate technical requirements, which affects the quality and increases the production cost of mobile learning applications. For the development of effective and successful mobile learning applications, it is important to identify set of technical quality requirements for mobile learning applications. With this work, we developed a new framework to capture most crucial technical quality dimensions and requirements for the development of mobile learning applications. To better understand and identify the list of technical quality dimensions and requirements a Delphi study was carried out. This method allowed us to reach a consensus in three rounds and counted with the participation of 30 experts in the Software Engineering, Information Systems and mobile learning fields. As a result of the Delphi study, a specific framework comprised by 19 technical quality requirements divided in six quality dimensions was developed for the development of mobile learning applications. This framework is expected to guide the designers and developers for a successful development process of mobile learning applications.
Keywords:	Technical Quality Requirements; Mobile Learning Applications; Delphi Study ;Software Engineering
Source:	Journal of Theoretical and Applied Information Technology 30^st October 2018 -- Vol. 96. No. 20 -- 2018
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Title:	FEATURE SELECTION METHODS FOR PREDICTING THE POPULARITY OF ONLINE NEWS: COMPARATIVE STUDY, AND A PROPOSED METHOD
Author:	SAMAH OSAMA M. KAMEL, MOHAMED NOUR
Abstract:	Nowadays, accessing the Internet has become interesting for the people’s life. It will be promising if it can accurately predict the popularity of news prior to its publication. Online classification is well suited for learning from large and high dimensional dataset. The main objective of this research work is to predict and evaluate the popularity of online news. Several approaches of feature selection will be adopted to reduce the dataset to improve the classification and prediction accuracy. Some filtering approaches will be used such as correlation, information gain and relief to remove the non-important features so that the classification of new instances will be more accurate. The above mentioned approaches will be presented for selecting the most significant features in the dataset and then providing comparison among their performance. Moreover, Bayes Network and K-Nearest Neighbors algorithms are trained for classification and prediction. The training set is used to construct the models while the testing set is used for validation. This work will be operated and tested using a dataset taken from the UCI machine learning repository containing thousands of articles with sixty-two attributes. A feature selection method is proposed based on features' extraction and/or features' fusion. A comparative study is done among the adopted methods and the novel proposed one. The performance of the adopted classification and prediction models and/or approaches will consider some measurable criteria such as precision, recall, accuracy and error for highlighting the advantages and disadvantages of the adopted approaches and the proposed one. From the experimental work, the performance of the proposed method is promising and outperforms those adopted ones.
Keywords:	Feature Selection, Classification Methods, Popularity Prediction, High Dimensional Datasets, and Online News.
Source:	Journal of Theoretical and Applied Information Technology 30^st October 2018 -- Vol. 96. No. 20 -- 2018
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Title:	CONTRIVING THE IS/IT MANEUVERS TO ENHANCE BUREAUCRATIC REFORM IN INDONESIAN GOVERNMENT
Author:	ARFIVE GANDHI, YOVA RULDEVIYANI, YUDHO GIRI SUCAHYO
Abstract:	Information System/Information Technology (IS/IT) has important role to accelerate and enhance bureaucratic reform in government institutions. Ministry of Energy and Mineral Resources (MEMR) Republic of Indonesia requires IS/IT to improve accountability and reduce complexity of bureaucratic in public services. To ensure optimization on IS/IT resources and alignment with MEMR’s strategic objectives, all IS/IT maneuvers should be prepared using a Strategic Information Systems Planning. This study performs advance exploration regarding on how MEMR contrive IS/IT maneuvers to enhance bureaucratic reform in four IT domains: IT governance, IS application, IT infrastructure and IT human resources. The contrived maneuvers refer to the principles of bureaucratic reform and also business principles: Automation, Continuity, and Standardized, then organized in a roadmap which encompasses 2016 until 2020. Without neglecting other maneuvers, this study promotes IT Steering Committee and integration of similar IS applications as concern to enhance bureaucratic reform in MEMR.
Keywords:	Bureaucratic Reform, Electronic Government, Strategic Information Systems Planning, Strategic Planning for Information Systems, Public Service
Source:	Journal of Theoretical and Applied Information Technology 30^st October 2018 -- Vol. 96. No. 20 -- 2018
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