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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
February 2016 | Vol. 84 No.3

Title:	DATA CONFIDENTIALITY IN THE WORLD OF CLOUD
Author:	KHALID EL MAKKAOUI, ABDELLAH EZZATI, ABDERRAHIM BENI-HSSANE, CINA MOTAMED
Abstract:	Cloud computing is becoming an attractive technology thanks to its diverse benefits such as: reducing costs, sharing computing resources, service flexibility, etc. However, the concept of data security and privacy has become a major issue. Indeed, the key challenge is to ensure users that the cloud service provider may store and process the raw data confidentially. The fear of seeing sensitive raw data stored and used are the major barrier to cloud services adoption. The use of methods capable of ensuring storage confidentiality and data processing located in cloud servers appears to be an effective way to overcome this barrier and to build confidence in cloud services. This paper describes a layered model of cloud security and privacy, and some approaches used for secure data in cloud environment. Specifically, we will focus on the encryption methods that can ensure data storage confidentiality and another technique that can ensure both data storage confidentiality and data treatments.
Keywords:	Cloud Computing, Security, Privacy, Confidentiality, Symmetric key, Homomorphic Encryption
Source:	Journal of Theoretical and Applied Information Technology 29^th February 2016 -- Vol. 8. No. 3 -- 2016
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Title:	NON-CONTACT ELECTROCARDIOGRAM (ECG) SMART CHAIR FOR ST SEGMENT ELEVATION MYOCARDIAL INFARCTION DETECTION
Author:	TUERXUN WAILI, RIZAL MOHD.NOR , KHAIRUL AZAMI SIDEK , ADAMU ABUBAKAR
Abstract:	Myocardial infarction (MI) is a medical term for heart attack. MI are classified into ST-segment elevation MI (STEMI) or non ST-segment elevation MI (NSTEMI). The ST-segment elevation MI (STEMI) can be detected by analyzing the electrocardiography (ECG) result. However, an ECG device is only available in hospitals due to its cost and requires an expert to operate the device. A personal ECG device at home is therefore difficult to be acquired. For most STEMI cases, heart problems requires early detection and medication. Unfortunately, frequent visits to the hospital may not be possible for most people. A new way to have personalized ECG reading without the presence of an expert is therefore desirable. One method is to use a non-contact ECG signal detection technique that could help assess cases of heart problems or an initial apoplectic condition. A non-contact ECG chair framework for STEMI is proposed to empower patients in getting personalized assessment to their heart condition at any time. Patients can easily use the ECG device at the comfort of their home or in the office by just sitting on their chair. The ECG signal will automatically be captured and analyzed to intelligently diagnose the heart condition. The implementation of this concept will help the Malaysian community with early intervention by medical experts and significantly reduce the mortality rate.
Keywords:	Capacitive Sensor, Non-Contact Electrocardiogram, ST Segment Elevation, Myocardial Infarction
Source:	Journal of Theoretical and Applied Information Technology 29^th February 2016 -- Vol. 8. No. 3 -- 2016
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Title:	ALGORITHM APPLICATION SUPPORT VECTOR MACHINE WITH GENETIC ALGORITHM OPTIMIZATION TECHNIQUE FOR SELECTION FEATURES FOR THE ANALYSIS OF SENTIMENT ON TWITTER
Author:	MOCHAMAD WAHYUDI, DWI ANDINI PUTRI
Abstract:	Twitter has become one of the most popular micro-blogging platform, recently. Millions of users can share their thoughts and opinions about various aspects and activites. Therefore, twitter considered as a rich source of information for decision-making and sentiment analysis. In this case, the sentiment is aimed to overcome the problem of automatically classifying user tweets into positive opinion and negative opinion. The classifier Support Vector Machine (SVM) used in this study is a machine learning technique that is popular text classifiers, as Support Vector Machine (SVM) algorithm is one that has a linear calcification of the main principles for determining the linear separator in the search space that can best separate the two classes different. But the Support Vector Machine (SVM) has the disadvantage that the appropriate parameter selection problem. The tendency in recent years is to simultaneously optimize the features and parameters for Support Vector Machine (SVM), so as to improve the accuracy of classification on Support Vector Machine (SVM). Genetic Algorithm has the potential to produce better features and becomes optimal parameters at the same time. This research generate text classification in the form of positive and negative tweets on twitter. Measurement accuracy is based on Support Vector Machine (SVM) before and after using a Genetic Algorithm. Evaluation was performed using 10 fold cross validation while accuracy is measured by the confusion matrix and ROC curves. The results of the study showed an increase in accuracy of Support Vector Machine (SVM) from 63.50% to 93.50%.
Keywords:	Sentiment Analysis, Twitter, Support Vector Machine (Svm), Classification Text
Source:	Journal of Theoretical and Applied Information Technology 29^th February 2016 -- Vol. 8. No. 3 -- 2016
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Title:	A HEURISTIC APPROACH TO INDOOR LOCALIZATION USING LIGHT EMITTING DIODES
Author:	MUHAMMAD SAADI, YAN ZHAO, LUNCHAKORN WUTTISTTIKULKIJ, MUHAMMAD TAHIR ABBAS KHAN
Abstract:	Widespread applications of location based services for indoor environments have created an opportunity for researchers to develop new techniques for accurate position estimation with less complexity. In this paper, we present a heuristic approach to localization by employing clustering for an indoor environment. Depending upon the number of light emitting diodes (LEDs) used as transmitter, level 1 clustering is achieved by simply comparing the signal strength for each combination of transmitter�s light intensities at the receiver. For level 2 clustering, a new technique of clustering is proposed, named portion clustering, is applied to further partition the area where the object of interest can be located. From the simulation results, it can be observed that the location estimation up to 16 centimeters can be achieved for an indoor environment with the dimensions of 3 � 3 � 3 using LEDs.
Keywords:	Localization, Light Emitting Diode, Machine Learning, Clustering, Received Signal Strength
Source:	Journal of Theoretical and Applied Information Technology 29^th February 2016 -- Vol. 8. No. 3 -- 2016
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Title:	DESIGNING AND IMPLEMENTING PARSING FOR AMBIGUOUS SENTENCES IN INDONESIAN LANGUAGE
Author:	DEWI SOYUSIAWATY, EKO ARIBOWO
Abstract:	In the daily life there are a lot of ambiguous words or sentences. For instance, in Indonesian language the word �apel� has two different meanings if it is placed in the sentence. It may mean 1) to hold a ceremony or 2) a name of a fruit. Another example is the word �tahu� that may mean 1) understand or know or 2) a name of a food from soybean. The ambiguous sentences become a matter in the translation application or dictionary if the application has no facility to detect the sentence with some different meanings. As a result, it will influence the translation result. The word �tahu� in the sentence �saya ingin tahu�, if it is translated into one of regional language such as Javanese language, it may result �kula kepengen tahu� (I want a food from soybean) or �kula kepengen weruh� (I want to know). It depends on what �tahu� means. This research discusses the role of parsing as the sentence breaker in identifying the ambiguous sentences, so the real meaning of the sentence can be obtained and the congruence between structure pattern of a sentence that is inputted and grammar rules saved can be acknowledged. The research started by collecting Indonesian language grammar rule data consisting of clause structure forming a sentence, phrase that is two or more words structure, and detail clause pattern structure including ambiguous phrases and vocabularies list. Then, flowchart for parsing is designed in some stages those are obtaining pattern and checking the phrase, implementing and evaluating the application. The research resulted the sentence parsing flowchart, application for ambiguous sentences checking and to know the structure congruence between the input sentence and the rules.
Keywords:	Parsing, Sentence, Ambiguous, Clause, Phrase
Source:	Journal of Theoretical and Applied Information Technology 29^th February 2016 -- Vol. 8. No. 3 -- 2016
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Title:	NER IN ENGLISH TRANSLATION OF HADITH DOCUMENTS USING CLASSIFIERS COMBINATION
Author:	MOHANAD JASIM JABER , SAIDAH SAAD
Abstract:	There is a need to retrieve and extract important information in order to fully understanding the ever-increasing volume of English translated Islamic documents available on the web. There is limited research focused on Named Entity Recognition (NER) for Islamic translations even though NER has seen widespread focus in other languages. Translated named entities have their own characteristics and available annotated English corpora do not cover all the transliterated Arabic names, which makes translations with NER difficult in the Islamic domain. This research addressed the use of NER in English translations of Hadith texts. The objective of this research was to design and develop a model that was able to excerpt Named Entities from English translation of Hadith texts. This research used supervised machine learning approaches, like Support Vector Machine (SVM), Maximum Entropy Classifier (ME) and Naive Bayes (NB), which were later combined via majority voting algorithm to identify named entities from Hadith texts. From the results of this research, voting combination approaches outmatched single classifiers with an overall F-measure of 95.3% in identifying named entities. The results indicated that combined models paired with suitable features were better suited to recognize named entities of translated Hadith texts as compared to baseline models.
Keywords:	Named Entity Recognition, supervised machine learning, Hadith text
Source:	Journal of Theoretical and Applied Information Technology 29^th February 2016 -- Vol. 8. No. 3 -- 2016
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Title:	INTELLIGENCE INTEGRATION OF PARTICLE SWARM OPTIMIZATION AND PHYSICAL VAPOUR DEPOSITION FOR TiN GRAIN SIZE COATING PROCESS PARAMETERS
Author:	MU�ATH IBRAHIM JARRAH1, ABDUL SYUKOR MOHAMAD JAYA, MOHD ASYADI AZAM, MOHAMMED H. ALSHARIF, MUHD. RAZALI MUHAMAD
Abstract:	Due to increasing complexity of industrial production, decisions regarding selection of coating parameters importantly influence the level of production, Optimization of thin film coating parameters is important in identifying the required output. Two main issues of the process of physical vapor deposition (PVD) are manufacturing costs and customization of cutting tool properties. The aim of this study is to identify optimal PVD coating process parameters. Three process parameters were selected, namely nitrogen gas pressure (N2), argon gas pressure (Ar), and Turntable Speed (TT), while thin film grain size of titanium nitrite (TiN) was selected as an output response. Coating grain size was characterized using Atomic Force Microscopy (AFM) equipment. In this paper, to obtain a proper output result, a developed quadratic polynomial model equation which represents the process variables and coating grain size was used in order to optimize the coating process parameters, particle swarm optimization (PSO) was used for optimization work. Finally, the models were validated using actual testing data to measure model performances in terms of residual error and prediction interval (PI). The result indicated that for response surface methodology (RSM), the actual coating grain size of validation runs data fell within the 95% (PI) and the residual errors were less than 10 nm with very low values, the prediction accuracy of the model is 96.09%. In terms of optimization and reduction the experimental data, PSO could get the best lowest value for grain size than experimental data with reduction ratio of ≈6%.
Keywords:	TiN, Grain Size, Modeling, Sputtering, PVD, RSM, PSO.
Source:	Journal of Theoretical and Applied Information Technology 29^th February 2016 -- Vol. 8. No. 3 -- 2016
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Title:	IMPLEMENTATION TWOFISH ALGORITHM FOR DATA SECURITY IN A COMMUNICATION NETWORK USING LIBRARY CHILKAT ENCRYPTION ACTIVEX
Author:	MUCH AZIZ MUSLIM, BUDI PRASETIYO, ALAMSYAH
Abstract:	Cryptography is required to secure the data networks communication. This study implements Twofish cryptographic algorithm using library Chilkat Encryption ActiveX Ms. Visual Basic. Twofish operate on a block of plaintext consisting of 128 bits. There are 3 steps in Twofish algorithm, the first step is divide input bit into 4 parts, the second step was performed XOR operation between bit input with a key, and the third step processing the input bits in 16 times Feistel network. To facilitate the implementation of the coding in Ms. Visual Basic we use Chilkat Encryption ActiveX. This research using agile methods with phases: plan, design, code, test, and release. Twofish algorithm implementation using Ms. Visual Basic and library Chilkat Encryption ActiveX can be used to secure the data. The data succeed to be encrypted or decrypted and irreversible. The program can be implemented to maintain the confidentiality of the data when transmitted over the Internet. The speed encryption process need 3 times longer than the decryption. Average of time in encryption process need 0,365 second, while decryption process need 0,0936 second.
Keywords:	Data security, Twofish, Chilkat Encryption ActiveX
Source:	Journal of Theoretical and Applied Information Technology 29^th February 2016 -- Vol. 8. No. 3 -- 2016
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Title:	ENHANCEMENT OF CLOUD PERFORMANCE AND STORAGE CONSUMPTION USING ADAPTIVE REPLACEMENT CACHE AND PROBABILISTIC CONTENT PLACEMENT ALGORITHMS
Author:	AHMED SALIH MAHDI, RRAVIE CHANDREN MUNIYANDIH
Abstract:	Infrastructure as a service (IaaS) is one of the most well-known cloud services. It facilitates high levels of flexibility in virtual machines (VMs). One of the challenges in cloud services is the effective management of large amounts of VM images. Cloud input-output (IO) performance significantly affects VMs, and significant storage resources are required, leading to higher management costs. Currently optimization is accomplished by two methods, involving either improving performance or decreasing image size, but low consumption of storage resources and achieving high levels of IO performance cannot be accomplished at the same time. Zone-based methods can potentially balance these requirements. The method proposed in this paper involves the use of adaptive replacement cache (ARC) and probabilistic content placement (PROB) algorithms, which together are known as zone based-adaptive replacement cache and probabilistic content placement (ZB-ARCPROB). This method provides more support to the cache management of images while considering all means of achieving high IO performance and low storage consumption. The research reported in this paper evaluated the ZB-ARCPROB method in relation to cloud performance using Network Simulator version 2.35 (NS2). The performance of the ZB-ARCPROB method was compared with zone-base method in terms of three metrics, namely IO latency, IO throughput, and relative storage consumption. This method is not only methodologically valid, but also offers the prospect of attracting interest from academia and industry. The results of the comparison indicate that the proposed ZB-ARCPROB method outperforms the zone-base method.
Keywords:	cloud computing, virtual machine (VM), image storage, adaptive replacement algorithm (ARC), probabilistic content placement
Source:	Journal of Theoretical and Applied Information Technology 29^th February 2016 -- Vol. 8. No. 3 -- 2016
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Title:	A PROPOSED FRAMEWORK TO SUPPORT ADAPTIVITY IN ONLINE LEARNING ENVIRONNMENT: USE CASE IN LMS
Author:	AIMAD QAZDAR, B.ER-RAHA, C. CHERKAOUI, A. BAKKI, D. MAMMASS
Abstract:	Online Learning Environments (OLE) such as LMS, MOOC and ALS are becoming increasingly popular in many educational institutes like universities. However, LMSs and MOOCs provide the same content for all learners in a given course. Educational theory suggests that learners possess different proprieties such as background, preference, cognitive level and style of learning. This paper investigates an experiment of implanting the adaptation in these environments. The goal is to propose a model of adaptation taking into account several dimensions of adaptation. We will so examine these dimensions in the context of hybrid systems consisting of LMSs, MOOCs and ALSs.
Keywords:	Adaptation, Adaptive Learning Systems, Learning Management System, Massive Open Online Cours, Learning Content, Adaptation Engine, Online Learning Environnement, AeLF
Source:	Journal of Theoretical and Applied Information Technology 29^th February 2016 -- Vol. 8. No. 3 -- 2016
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Title:	QUERY SYSTEM OF GENERATED ONTOLOGICAL MODELS FROM TRADITIONAL DATA SOURCES
Author:	WIDAD JAKJOUD, MOHAMAD BAHAJ
Abstract:	The cooperation of ontologies, as sources of knowledge, and traditional data sources are used to defeat the heterogeneity of information systems in terms of integration of information. Also, this cooperation allows the exploitation of classic web resources by inference agents. In this paper, we focus on ontologies generated from traditional data sources. Our goal is to query an ontological model without having to populate ontologies with instances from data source. The proposed system adds an intermediate level of abstraction between the ontological model and the data source schemas, this level can generate partially and temporarily the data in XML format. The system also provides a SPARQL-XQUERY mapping which rewrites any SPARQL query at XQUERY query in order to be executed on already generated data.
Keywords:	SPARQL, XQUERY, mapping, model, ontology, data source
Source:	Journal of Theoretical and Applied Information Technology 29^th February 2016 -- Vol. 8. No. 3 -- 2016
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Title:	A ZERO-DISTORTION FRAGILE WATERMARKING SCHEME TO DETECT AND LOCALIZE MALICIOUS MODIFICATIONS IN TEXTUAL DATABASE RELATIONS
Author:	ABD. S. ALFAGI , A. ABD. MANAF , B. A. HAMIDA , R. F. OLANREWAJUB
Abstract:	In this paper, we present a new zero-distortion fragile watermarking scheme to detect and localize malicious modifications in textual database relations. Most existing fragile watermarking schemes introduce errors or permanent distortion into the original database content. These distortions violate the integrity of the database consequently the database quality and usability are degraded. Although, some fragile schemes are able to authenticate the database integrity and detect the malicious modifications made on the database but they are either tuples or attributes ordering based and unable to characterize the attack, identify the type of attack, identify the tampered data and locating the tampered tuples. In addition, most existing fragile schemes are based on LSB or MSB in generating the watermark unlike to this scheme, which is based on local characteristics of the relation itself such as frequencies of characters and text length in generating the watermark. This scheme is serviceable for sensitive and insensitive textual relational database since it does not introduce any error into the original contents. In addition, this scheme overcomes the weaknesses of data integrity violate, data usability and data quality degradation. The experimental results show the ability of proposed scheme in authenticating the database relation as well as the ability of characterize the attack, identifying the changed data and locating the text that affected by the malicious modification without depend on tuples and attributes ordering.
Keywords:	Database Watermarking, Fragile Watermarking Scheme, Robust Watermarking Scheme, Tamper Detection, and Authentication
Source:	Journal of Theoretical and Applied Information Technology 29^th February 2016 -- Vol. 8. No. 3 -- 2016
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Title:	BINARY RELEVANCE (BR) METHOD CLASSIFIER OF MULTI-LABEL CLASSIFICATION FOR ARABIC TEXT
Author:	ADIL YASEEN TAHA, SABRINA TIUN
Abstract:	Multi-label text classification has become progressively more important in recent years, where each document can be given multiple labels concurrently. Multi-label text classification is a main challenging task because of the large space of all potential label sets, which is exponential to the number of candidate labels. Among the disadvantages of the earlier multi-label classification methods is that they typically do not scale up with the number of specific labels and the number of training examples. A large amount of computational time for classification is required for a large amount of text documents with high dimensionality, especially, the Arabic language which has a very complex morphology and rich in nature. Furthermore, current researches have paid a little attention to the multi-label classification for Arabic text. Hence, this study aims to design and develop a new method for multi-label text classification for Arabic texts based on a binary relevance method. This binary relevance is made up from a different set of machine learning classifiers. The four multi-label classification approaches, namely: the set of SVM classifiers, the set of KNN classifiers, the set of NB classifiers and the set of the different type of classifiers were empirically evaluated in this research. Moreover, three feature selection methods (Odd ratio, Chi-square and Mutual information) were studied and their performances were investigated to enhance the performance of the Arabic multi-label text classification. The objective is to efficiently incorporate classification algorithms and feature selection to create a more accurate multi-label classification process. To evaluate the model, a manually standard interpreted data is used. The results show that the machine learning binary relevance classifiers which consists from a different set of machine learning classifiers attains the best result. It has achieved a good performance, with an overall F-measure of 86.8% for the multi-label classification of Arabic text. Besides, the results show an important effect from the used feature selection methods on the classification. Distinctly, the set of the different set of algorithms proves to be an efficient and suitable method for the Arabic multi-label text classification.
Keywords:	Arabic Text Classification, Multi-label Classification, Feature Selection, Statistical Methods
Source:	Journal of Theoretical and Applied Information Technology 29^th February 2016 -- Vol. 8. No. 3 -- 2016
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Title:	DYNAMIC MEMORY ALLOCATION USING FREE BLOCKS
Author:	ALEKSANDR BORISOVICH VAVRENYUK, IGOR VLADIMIROVICH KARLINSKY, ARKADY PAVLOVICH KLARIN, VIKTOR VALENTINOVICH MAKAROV, VIKTOR ALEKSANDROVICH SURIGIN
Abstract:	Algorithms for the dynamic allocation of RAM (Random Access Memory) to the operating system when multiprogramming have a significant impact on the efficiency of the operating system as a whole. Memory Manager (allocator) of GNU C Library UNIX standard library, which claims universality, is ineffective in some cases. This article describes the allocator algorithm with a list of clear areas, proposed by the authors, which allows achieving a higher efficiency of the RAM usage. The test methodology is proposed for the developed allocators, and the results of the comparison of the proposed allocator with the allocator of the GNU C Library UNIX standard library are provided.
Keywords:	Allocator, Memory Manager, The Process Of Memory Allocation, Memory Fragmentation, Operating Systems
Source:	Journal of Theoretical and Applied Information Technology 29^th February 2016 -- Vol. 8. No. 3 -- 2016
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