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Submit Paper / Call for Papers
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).
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Journal of
Theoretical and Applied Information Technology
June 2021 | Vol. 99
No.12 |
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Title: |
INTELLIGENT SYSTEM AND OPTIMAL MINIMISATION OF ENERGY CONSUMPTION ON THE
ATTITUDE CONTROL OF A VTOL UAV HEXACOPTER BASED ON FRACTIONAL CONTROL LAWS |
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Author: |
S.ENNIMA, S.BOUREKKADI, O.EL IMRANI , I.BAKKALI , H.CHIKRI , A.ELGHARAD |
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Abstract: |
The objective of this research study based on numerical results is to validate
the feasibility and effectiveness of a new method for controlling hexacopter
type UAVs, which belong to the family of multirotors established on laws
fractional control (FOC) , taking into consideration an intelligence system for
smart cities that will have economic impacts in the future. the control method
asserts advantages regarding of response time and stabilisation at the desired
altitude and attitude. This control is intended to be used to control and
maintain the desired trajectory during several manoeuvres while minimising
energy consumption. The system's performance and stability are analysed with
several tests, from simple hovering flight. This new solution applied to
multi-rotor UAVs will totally revolutionise this technology in terms of
stability and solve the problem for many industries. All the simulations
discussed in this article were performed in the MATLAB/Simulink environment. |
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Keywords: |
Drone, Unmanned Aerial Vehicle (UAV), Hexacopter, Smart Cities , Intelligent
Systems, Fractional Order Control (FOC). |
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Source: |
Journal of Theoretical and Applied Information Technology
30th June 2021 -- Vol. 99. No. 12 -- 2021 |
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Title: |
NO HAMBURGERS FOR THE ELDERLY? BASED ON REGRESSION ANALYSIS METHOD |
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Author: |
MENG JIAJIA, OOK LEE |
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Abstract: |
Since the 21st century, China has become a super aging society, and researchers
have focused on societal burdens from a problem perspective, as well as new
market opportunities attuned to the perspectives and needs of the elderly,
creating a new mode of life, smart products and services. However,product
development trends indicate a need for adaptation, affordances, and an inclusive
design approach. This paper presents a case study of elderly ordering meals in
the hamburger shop through the self-service ordering machine, aims to research
the differences in user interface requirements between the elderly and young
people by combining the consumption characteristics of the elderly learned from
the literature. In this paper, I issued the questionnaires to get the
evaluations of the elderly and young people on the satisfaction of the design of
the hamburger shop's self-service ordering interface, and further concluded the
differences in user interface requirements between the elderly and young people
in the same scenario with some practical suggestions after finding out the
difference in operation interfaces for the elderly and young people through
linear regression method. We hope that this paper will draw the attention of the
market and merchants to make optimization, thus improving the dining experience
and the user proportion of the elderly in the restaurant market. |
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Keywords: |
The Elderly; Super Aging; Interface Design; elderly UI;Linear Rregression
Analysis; Kiosk |
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Source: |
Journal of Theoretical and Applied Information Technology
30th June 2021 -- Vol. 99. No. 12 -- 2021 |
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Title: |
USING MACHINE LEARNING MODELS TO COMPARE VARIOUS RESAMPLING METHODS IN
PREDICTING INSURANCE FRAUD |
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Author: |
MOHAMED HANAFY, RUIXING MING |
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Abstract: |
One of the most common types of fraudulent is insurance fraud. And in particular
fraud in automobile insurance, the cost of automobile insurance fraud is
substantial for property insurance companies and has a long-term impact on
insurance firms' pricing strategies. And In order to minimize insurance rates,
car insurance fraud detection has become necessary. Although predictive models
for the detection of insurance fraud are in active use in practice, there are
relatively few documented studies on the use of machine learning approaches to
detect insurance fraud, likely due to the lack of available data. In this paper,
by using real-life data, we evaluate 13 machine learning approaches. And Because
of the imbalanced datasets in this area, predicting insurance fraud has become a
significant challenge. Due to our data consist mostly of a "non-fraud claims "
class with a small percentage of "fraud claims. " Thus that the prediction of
fraud appears weakly with classification models; therefore, the present study
seeks to suggest an approach that enhances machine learning algorithms' results
by using resampling techniques, such as Random Over Sampler, Random under
Sampler, and hybrid methods, to address the issue of unbalanced data. And we
compare between them. This paper shows that after using resampling techniques,
the efficiency of all ML classifiers is enhanced. Furthermore, the findings
confirm that there is no one resampling method that overall outperforms.
Besides, among all the other models, the Stochastic Gradient Boosting classifier
obtained the best result when using the hybrid resampling technique. |
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Keywords: |
Automobile Insurance; Insurance Fraud; Fraud Detection, Classification; Machine
Learning; Imbalanced Data; Resampling Methods. |
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Source: |
Journal of Theoretical and Applied Information Technology
30th June 2021 -- Vol. 99. No. 12 -- 2021 |
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Title: |
THE IP CHANNEL BANDWIDTH DURING TRANSMISSION OF THE VIDEO AND TOMOGRAPHY SIGNALS |
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Author: |
PAVEL DUNAYEV, SERGEY ABRAMOV, KANIBEK SANSYZBAY, AIGERIM KISMANOVA |
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Abstract: |
The aim of the study is to develop a confident algorithm for assessing the
bandwidth of an IP channel affecting image quality during transmission of the
video signal and signals for tomography. The research method is based on the
Monte Carlo method. The development of an algorithm for assessing the bandwidth
based on information identifier (IP packet delay time and delay variation) is
discussed in this paper. The experiments have been carried out taking into
account the size of the information packet of the video signal and the signals
for tomography. The outcomes of this study embrace the developed model of an IP
channel, its software implementation, which allows assessing the dynamic
bandwidth. The developed model enables to perform comparison of the efficiency
of a compressor, a router, and a server with digital signal processing by the
criterion of confidence of packet servicing time in the IP channel. Analytical
calculations have been carried out for the purpose of quantitative calculation
of the obtained confidence to confirm the results of modelling. The results of
modelling allow taking into account the main interrelated factors that appear in
the form of distortions in the image during the transmission of video signals
and signals for tomography. The article discusses the results of the “Analysis
of the functioning features of multi-service IP networks” project. The present
paper reveals new knowledge about the development of confident algorithms that
allow assessing the probability of delivery, packet loss, and IP channel
bandwidth with a given probability. In prospective, these studies are necessary
and relevant for performing remote surgical operations and decoding tomography
images remotely. |
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Keywords: |
Video signal, Signal for Tomography, IP Channel, Image Quality, Bandwidth,
Algorithm, Confidence |
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Source: |
Journal of Theoretical and Applied Information Technology
30th June 2021 -- Vol. 99. No. 12 -- 2021 |
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Title: |
DETECTION OF ACCESSIBILITY AND QUALITY OF WEBSITES OF THE LEADING UNIVERSITIES
ОF THE WORLD |
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Author: |
MARIANA SASHNOVA, ANDREII ZAHORULKO, SVITLANA LIULCHAK, TETIANA SHABELNYK, ALONA
KOLOMIIETS, SVITLANA YERMAKOVA |
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Abstract: |
Accessibility level of websites of leading educational institutions’ websites
has been determined through analysing compliance with the levels of
accessibility under WCAG 2.1; the results obtained enable to develop
hierarchical model of accessibility evaluation taking into account criteria and
sub-criteria factors. Qualitative formation of the electronic system of
education in fundamental and technical disciplines shall enable to provide
students, regardless of health defects, with high-quality education, ensuring
development of European countries in the sphere of science in accordance with
international standards.
High quality of the websites of the following
educational institutions has been detected: 3% for the University of Michigan
Ann Arbor and 6% for the University of Cambridge, for other educational
institutions it is in range from 13% to 38% (for 40 scanned pages). The website
of U701 University for
100 scanned pages is characterized by minimum of 9%
accessibility, 2% compatibility and 31% compliance with web standards.
Massachusetts Institute of Technology has 35 pages with the problem of
accessibility. National Technical University “Ihor Sikorskyi Kyiv Polytechnic
Institute” has 22 pages with accessibility problem. Low accessibility level has
been detected at Lviv Polytechnic National University; it has 80 pages of the
website with problems for users, including those with disabilities. The proposed
hierarchical model of evaluation of quality of websites by criteria and
sub-criteria factors shall form accessible websites to users, improve access to
them regardless of functional disorders, reducing the duration and effort to
search for information. |
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Keywords: |
WCAG 2.1, AA level, SortSite, website, W3C, hierarchical model |
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Source: |
Journal of Theoretical and Applied Information Technology
30th June 2021 -- Vol. 99. No. 12 -- 2021 |
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Title: |
ARTIFICIAL INTELLIGENCE APPLICATIONS FOR COVID-19 PANDEMIC: A REVIEW |
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Author: |
HAMZEH MOHAMMAD ALABOOL, DEEMAH ALARABIAT, MOHAMMAD HABIB |
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Abstract: |
The number of AI techniques has increased greatly for containment COVID-19. AI
techniques differ in terms of purpose, synthesis methods, datasets, and
validation approach. This increase and diversity in the numbers of proposed AI
techniques can confuse decision makers and lead them to the dilemma of what is
the appropriate technique under the specific conditions. Yet, studies that
assess, analyze, and summarize the unresolved problems and shortcomings of
current AI techniques for COVID-19 are limited. In the existing review studies,
only individual parts of AI techniques, rarely the full solution, are reviewed
and examined. Thus, this study aims to present a comprehensive systematic review
on the application of AI techniques in containment the COVID-19 pandemic. The
applied search strategy led to include 73 papers related to the Application of
AI techniques for COVID-19 published from December 2019 to August 2020. Ten
applications of AI for containment COVID-19 were identified. In addition, the
analysis results of the systematic review revealed five deficiencies so that
future research should take them into consideration. |
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Keywords: |
COVID-19; Coronavirus; SARS-CoV-2; Artificial Intelligence, Healthcare, Review |
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Source: |
Journal of Theoretical and Applied Information Technology
30th June 2021 -- Vol. 99. No. 12 -- 2021 |
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Title: |
IMPLEMENTATION OF THE BFS ALGORITHM AND WEB SCRAPING TECHNIQUES FOR ONLINE SHOP
DETECTION IN INDONESIA |
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Author: |
NURDIN, BUSTAMI, 3MUHAMMAD HUTOMI, MARISCHA ELVENY, RAHMAD SYAH |
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Abstract: |
This The number of online shops in Indonesia on the Shopee e-commerce web makes
it difficult for consumers to detect the authenticity of online stores. This
online shop detection system is an application to detect genuine online shops or
fake online stores (dropship). This study aims to assist consumers in the
process of searching for genuine online stores that sell the desired products
quickly and automatically. The method used in this research is the Breadth First
Search (BFS) algorithm and the Web Scraping technique which will be applied to
the Shopee e-commerce web in Indonesia based on three parameters, namely
delivery, store rating, and response rate. The results of this study indicate
that the Breadth First Search algorithm with the Web Scraping technique can be
used to complete the process of retrieving store data and product data in
e-commerce and is able to explore as well as check online stores automatically
with good performance. The test results are based on factors such as precision,
recall, F-Score, and Accuracy, with the results of 81% precision, 89% recall,
84.82% f-score, and 90% accuracy with 100 search data. |
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Keywords: |
Online Shop, BFS Algorithm, Web Scraping, E-Commerce, Detection |
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Source: |
Journal of Theoretical and Applied Information Technology
30th June 2021 -- Vol. 99. No. 12 -- 2021 |
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Title: |
SMART HOME AND MACHINE LEARNING FOR MEDICAL SURVEILLANCE: CLASSIFICATION
ALGORITHMS SURVEY |
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Author: |
LAMIAE ELOUTOUATE, ELOUAAI FATIHA, GIBET TANI HICHAM, BOUHORMA MOHAMMED |
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Abstract: |
With the recent advancements on the computer-engineering field, the paradigm of
smart home has been increasingly suggested as an empowering solution for various
issues. Smart home employs the most novel technologies, such as wearable
technologies, the Internet of Things (IoT), cloud computing and machine learning
analysis capabilities to change the way we live. Accordingly, a smart home for
medical surveillance would certainly reinforce the smart healthcare model, thus
making healthcare system further accomplished, more comfortable and
customizable. With the intent of creating a convenient smart home for medical
surveillance, in this paper, we first introduce a novel architecture for a smart
home aimed to monitor a patient specific health condition and update the health
practitioner with the patient data. Then, we exhibit a comparative study of
several machine-learning classification algorithms capable of classifying a
patient arising health condition and ultimately decide whether to raise a
concern notification, call for help or only log the information. |
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Keywords: |
Smart Home, Smart Healthcare, Machine Learning, Medical Surveillance, IoT |
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Source: |
Journal of Theoretical and Applied Information Technology
30th June 2021 -- Vol. 99. No. 12 -- 2021 |
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Title: |
DRAMATIC NARRATIVE AND STORYTELLING IN FINANCIAL PLANNER BRANDING THROUGH
INSTAGRAM |
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Author: |
NURUL ITQI, IWAN SUPRIYADI, LAMANI |
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Abstract: |
Based on theories of narrative paradigm by Walter Fisher, narrative and
narratology, and storytelling, this descriptive study analyses the narrative
content and storytelling on late Instagram of Jouska, the financial planning
company in Indonesia. This study aims to get an understanding of how Jouska
applied the narrative and storytelling criteria on its Instagram contents and
how the content could persuade the audience to make a set of good associations
linked to the brand in their mind. This qualitative content analysis collected
data by using maximum variation sampling to decide the population, and then
reduced it to get the sample. The coding frame was produced by using
concept-driven strategy to get main categories. They are the criteria of a good
narrative and storytelling based on theories: dramatic events, complex
narrative, retrospective evaluation, causal development, enthymemes, storyline,
responsive designed story, and catchy phrase. The complex narrative which most
of them posted on Instagram Stories is more likely to have the complete
criteria. The result of this qualitative content analysis shows that Jouska
contents did not always have all criteria of a good narrative. The result also
shows that the success of Jouska branding strategy due to dramatism in almost
all narrative content. |
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Keywords: |
Narrative; Storytelling; Instagram; Dramatism; Branding |
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Source: |
Journal of Theoretical and Applied Information Technology
30th June 2021 -- Vol. 99. No. 12 -- 2021 |
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Title: |
PERFORMANCE EVALUATION OF FOUR LEARNING-BASED AUTOMATIC IDENTIFICATION MODELS
FOR PAPAYA FRUIT CLASSIFICATION |
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Author: |
JONATHAN VELAZQUEZ, ANDRÉS MARTÍNEZ, FREDY MARTÍNEZ |
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Abstract: |
Colombia is a country with an economy strongly linked to agriculture. Besides,
thanks to its geographical characteristics, it has a wide variety of fruit
products of great commercial acceptance both domestically and internationally.
However, despite its strong economic dependence, this sector has not benefited
from adequate technological developments. One of the processes in the production
chain that in many cases is still carried out manually is the selection and
classification of the fruit. In the specific case of papaya (papaw or pawpaw),
this manual sorting strategy does not satisfy the quality of the process in
terms of efficiency and performance, triggering the productive stagnation of
this sector. This research proposes to support this process using an automatic
system through the use of a model based on neural networks. In particular, a
performance comparison is made between four neural topologies recognized for
their high categorization capacity. The selected topologies include a low depth
network and three deep learning structures. The models were trained with a
proprietary dataset consisting of three visually identifiable fruit states. As a
result, the high performance of the deep convolutional networks, in particular,
the ResNet and DenseNet networks, is observed, making them strong candidates for
the development of an autonomous embedded system. |
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Keywords: |
Automatic sorting, Deep learning, Fruits, Image classification, Neural networks |
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Source: |
Journal of Theoretical and Applied Information Technology
30th June 2021 -- Vol. 99. No. 12 -- 2021 |
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Title: |
THE EFFECTIVENESS OF DISTANCE PRACTICE LEARNING FOR FACING COVID-19 PANDEMIC IN
INDONESIA |
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Author: |
FEBRIKA YOGIE HERMANTO, SUTIRMAN, MAR ATUS SHOLIKAH, MEYLIA ELIZABETH RANU |
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Abstract: |
The Covid-19 pandemic has transformed learning that is usually conducted by
direct learning into indirect learning, especially distance learning. During the
Covid-19 pandemic, schools in Indonesia adjusted the learning to distance
learning. The purpose of this study is to determine the effectiveness of
distance practice learning and to find out what factors affect distance learning
conducted in vocational high schools for facing the Covid-19 pandemic in
Indonesia. This research was conducted by a mixed-method using the
pretest-posttest nonequivalent control group design and in-depth interviews to
dig the factors that influence the phenomenon. This research was conducted by
involving 53 students and 4 teachers in Yogyakarta. Test data were analyzed by
using the N-Gain Test, and interview data were analyzed using the Miles &
Huberman Model. The results of this study indicate that students who use
distance practice learning that is packaged with collaborative learning get
better cognitive results than direct practice learning, but students’ affective
and psychomotor assessment of distance practice learning gets a lower score than
direct practice learning, meanwhile, the score is a good category. The
phenomenon occurs due to the students' good understanding of utilizing
information technology contained on the internet, and the good communication
between students and teachers in completing practical assignments. |
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Keywords: |
Covid-19, Distance Learning, Practical Learning, Vocational High School |
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Source: |
Journal of Theoretical and Applied Information Technology
30th June 2021 -- Vol. 99. No. 12 -- 2021 |
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Title: |
USER EXPERIENCE ANALYSIS OF FERRY SERVICE EMPLOYEE TO USE OF THE HUMAN RESOURCE
INFORMATION SYSTEM |
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Author: |
AGUNG AYU CHANDRA, LUH PUTU AYU KRISTINA, YOHANNES KURNIAWAN |
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Abstract: |
The success of Human Resource Information System (HRIS) will greatly assist the
company in managing human resources, where the success of HRIS is due to
employee support to make improvements to the development of HRIS functions based
on employee needs. For this reason, this study is intended to measure the user
experience based on employee's perception related the role of HRIS in the
Company. Where the research model combines several previous studies with
approaches to Technology Acceptance Model (TAM) and the success of HRIS. The
results of the study show there is something new about the success of HRIS in
Ferry Company that are not affected by user satisfaction with the quality of the
system, on the other hand, the priority concerns of employees are the quality of
information, ease of use and perceived benefits of the HRIS. The next company
need to focus on improvement the quality of information on the website and
increasing the user experience of the HRIS website. |
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Keywords: |
HRIS, Information System, Perceive, User Satisfaction |
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Source: |
Journal of Theoretical and Applied Information Technology
30th June 2021 -- Vol. 99. No. 12 -- 2021 |
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Title: |
EFFECTIVENESS OF INFORMATION MEDIA FOR THE IMPROVEMENT OF INDONESIAN FARMERS’
KNOWLEDGE AND SKILLS |
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Author: |
ULANI YUNUS, MARIKO RIZKIANSYAH, ARLEEN ARIESTYANI, YOSSIE TRENANTO, SOPHIA ALIM |
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Abstract: |
This study develops problems in the Indonesian agricultural sector recently.
Based on this perspective, we examined how farmers could enhance information
media to improve their knowledge and skills. The theory that can be generated is
that the process of information educating will be successful if directed
according to the age and availability of technological facilities. The more
young and productive, the easier it will be to establish knowledge and skills
for certain objects. The use of Information and Communications Technology (ICT)
will be maximal if accompanied by the recipient of the message to adapt equipped
with motivation and perception of the information it receives. Data were
collected among 243 participants from 3 regions in Indonesia (Bangil, Lembang,
and Manado). The results showed that information media and farmers’ knowledge
had affected farmers’ skills. The majority of farmers still rely on information
from agricultural extension workers, especially in the Bangil region. While the
Manado Region still relies heavily on Television and Youtube. |
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Keywords: |
Information Media, Farmers, Knowledge, Skills |
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Source: |
Journal of Theoretical and Applied Information Technology
30th June 2021 -- Vol. 99. No. 12 -- 2021 |
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Title: |
WIRELESS MONITORING OF POWER CONSUMPTION FOR INDUSTRIAL ROBOT DURING A PICK AND
PLACE TASK FOR PREDICTIVE MAINTENANCE |
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Author: |
JAWAHER ABDULWAHAB FADHIL, AHMED FAEQ HUSSEIN, LATEEF ABD ZAID QUDR, and AHMAD
H. SABRY |
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Abstract: |
Industrial companies follow different maintenance strategies to increase
operational reliability and reduce costs. One way to reduce maintenance costs is
by real-time inspection of power consumptions to predict the potential failure
of industrial machines. Wireless monitoring is essential as it provides safe and
remote measuring for such applications. Related studies utilized efficient
devices and strategies for monitoring the energy consumption of industrial
machines, but didn't present a cost-effective and simple design accurately
monitoring the power for multi-degree of freedom (MDOF) robots. The objective of
this work is to develop a cost-effective wireless power consumption monitoring
system enhancing predictive maintenance purposes for MDOF industrial robots.
Unlike the traditional Zigbee-based WSN mentioned in the literature, the
presented scheme includes only two RF modules, a single remote-sensing node
called router XBee and another module at the monitoring station connected to a
PC. The key feature of this cost-effective design is the ability to measure,
process, and transfer data required to perform energy monitoring by only using
two modules. ABB-IRB-1200 robot manipulator is used as a practical platform to
test the effectiveness of the developed design. The measurement of power
consumption is conducted via performing a task called pick-and-place by the
robot. The produced consumption profile of the robot input power can be used
further for energy modeling and estimation. |
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Keywords: |
Five Power consumption, Monitoring, ZigBee, Wireless sensor network, industrial
robot. |
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Source: |
Journal of Theoretical and Applied Information Technology
30th June 2021 -- Vol. 99. No. 12 -- 2021 |
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Title: |
A COMPREHENSIVE APPROACH FOR CONVERTING RELATIONAL TO GRAPH DATABASE USING SPARK |
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Author: |
WAEL MOHAMED, MANAL A.ABDEL-FATTAH, SAYED ABDELGABER |
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Abstract: |
Nowadays, data processing requirements is growing exponentially, and relational
database is not always the best solution for all situations in big data such as
increasing growth of data. Thus, NoSQL databases emerged to overcome the
limitations of relational database and work with big data. NoSQL databases have
four types of models, namely, key-value model, document database, column
database, and graph database. Many approaches have been proposed to convert
relational database to NoSQL models. However, most of them map relational
database to key-value or column or document. Converting relational to graph
database is slightly disregarded by the researchers.
This paper proposes
a comprehensive approach, based on Spark framework, for transformation and
migration of relational database to graph database without semantic loss. The
approach also supports conversions from Sql commands to cypher commands .It is
categorized into two parts. The first part is concerned with “transformation and
migration using Spark”, which encompasses three phases: Meta data analyzer,
transformation algorithm, and migration algorithm. The second part focuses on
“SQL to cypher”, which divides into two phases: SQL parser and Translator. The
suggested approach has been applied, results and validation for the proposed
approach |
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Keywords: |
Big Data , NOSQL , Graph Database , Spark , Neo4j |
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Source: |
Journal of Theoretical and Applied Information Technology
30th June 2021 -- Vol. 99. No. 12 -- 2021 |
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Title: |
INTRODUCING A NOVEL INTEGRATED MODEL FOR THE ADOPTION OF INFORMATION SECURITY
AWARENESS THROUGH CONTROL, PREDICTION, MOTIVATION, AND DETERRENCE FACTORS: A
PILOT STUDY |
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Author: |
ISSAM AL-SHANFARI, WARUSIA YASSIN, RAIHANA SYAHIRAH ABDULLAH, NABIL HUSSEIN
AL-FAHIM, ROESNITA ISMAIL |
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Abstract: |
Information security (IS) violations have a negative impact at both
organisational and individual levels. Information security awareness (ISA)
therefore plays a positive role in ensuring employees adhere to an
organisation's security policies. The challenges that arise in protecting the
information infrastructure in the Omani public sector are increasing because of
a rise in cases of piracy and phishing attempts as well as a lack of adequate
ISA among employees. This paper discusses a pilot study from our ongoing
research that proposes an integrated model for adopting ISA as an effective
method to improve the security behaviour of employees in Omani institutions.
This study aims to validate the reliability of research instrument items prior
to conducting a main survey on the adoption of the ISA model in Oman. PLS-SEM
and SPSS software were used to conduct statistical analyses, which included a
skewness test, a correlation analysis, a Cronbach’s alpha test, and tests for
composite reliability (CR), average variance extracted (AVE), and discriminant
validity. Three main theories were utilised in the formation of the integrated
ISA model: the theory of planned behaviour (TPB), protection motivation theory
(PMT), and general deterrence theory (GDT) – along with two facilitating
condition-related constructs: organisational support and communication. The
findings indicated that all construct items for all variables have acceptable
Cronbach’s alpha values, composites reliability, AVE, and discriminant validity.
The results of this study reveal that the questions were applicable, subject to
one interpretation, to all participants. Hence, this study contributes to the
body of ISA literature by discussing ISA in terms of the bases of control,
prediction, motivation, and deterrence. This synthesis constitutes a new
perspective that enables organisations to better manage the ISA process,
particularly in Oman. |
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Keywords: |
Enhancing security awareness, Information security awareness, Pilot study,
PLS-SEM, Survey. |
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Source: |
Journal of Theoretical and Applied Information Technology
30th June 2021 -- Vol. 99. No. 12 -- 2021 |
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Title: |
A SYSTEMATIC REVIEW OF BUSINESS INTELLIGENCE THE SENTIMENTAL ANALYSIS ON THE
ONLINE MARKET |
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Author: |
ZAHRA DAHISH |
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Abstract: |
Obviously, social networking voices (VoC) for analysts able to perform
customer-driven business intelligence (BI) analysis have emerged as quality
evidence. However, to the best of the understanding of scholars, there is still
a shortage of study that deals with such impressive content sources and deals
with different accessible data from the BI science viewpoint (e.g., social
media, intellectual property). This analysis has therefore been aimed at
evaluating the applicability of social network data in BI research and
systematically reviewing the primary research papers in this area. This research
contrasts social network data in terms of data quality, processing, updating
capability and framework, with other accessible data (e.g. grey literature,
public service data), which is decided through a cautious discussion with
experts. Then, the research collected 57 papers from the Web of Science (WoS)
website centered on social networking, and three questions on details,
methodology, and findings have been examined with a view to unraveling the field
of analysis. The results are to educate current researchers regarding potential
research recommendations, encourage entrants to gain insight into the overall
analysis process of social media data, and offer practitioners environmentally
friendly approaches to social media analysis. |
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Keywords: |
Customer Behaviour, Business Intelligence, Online Reviews, Social Networking and
VoC |
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Source: |
Journal of Theoretical and Applied Information Technology
30th June 2021 -- Vol. 99. No. 12 -- 2021 |
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Title: |
A CZEKANOWSKI'S QUANTITATIVE INDEXED FUZZY BROWN BOOST DATA CLUSTERING FOR WIND
POWER PREDICTION IN SMART GRID |
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Author: |
JENCY W.G , DR. JUDITH J.E |
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Abstract: |
Wind power prediction has received greater attention recently for generating
energy continuously and sustainably and therefore new functions of electricity
networks are necessitated. Smart grid is certainly in the evolution of renewable
energy. This paper proposes a novel technique called Czekanowski's Quantitative
Indexed Fuzzy Brown Boost Data Clustering (CQIFBBDC) is proposed with the
objective of to increase the wind power prediction performance with higher
accuracy and acceptable time consumption. The CQIFBBDC technique initially
identifies essential energy feature for power prediction from the wind farm
database using Czekanowski's quantitative index so that equilibrium between
creation and electricity consumption is ensured therefore reducing the
prediction time. After that, Fuzzy Brown Boosting Data Clustering of wind power
is integrated into smart grids for predicting wind power according to the
characteristics of wind turbines. Fuzzy Brown Boosting Data clustering process
is carried out to group the input wind data in the smart grid using a FLAME
clustering method. The FLAME clustering algorithm performs the clustering
process based on neighborhood relationships between the data using a fuzzy
triangular membership function. The Brown Boost method combines the results of
weak learners to increase the clustering performance with reliability and
efficiency of grid operation put forward exorbitant specifications for precise
and accurate prediction. |
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Keywords: |
Wind Power Prediction; Feature Selection; Czekanowski's Quantitative Index;
Brown Boost Clustering; FLAME Clustering Algorithm; Fuzzy Triangular Membership
Function |
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Source: |
Journal of Theoretical and Applied Information Technology
30th June 2021 -- Vol. 99. No. 12 -- 2021 |
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Title: |
ISSUES AND CHALLENGES FROM TEACHERS’ PERCEPTIONS IN CREATING ONLINE LEARNING IN
THE MIDST OF COVID-19 PANDEMIC |
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Author: |
CHE KU NURAINI CHE KU MOHD, FAAIZAH SHAHBODIN |
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Abstract: |
The outbreak of the Corona virus during the month of December 2019 spread to
various parts of the planet in a few months brought our lives to a halt. Along
with the extreme health crisis faced by COVID-19, the education sector was
severely impacted. This study explores the perceptions of secondary school
teachers of online learning in a program developed in Malaysia during the
COVID-19 Pandemic. A quantitative survey was conducted to evaluate teachers'
perceptions of teaching and learning engagement. Data have been obtained by a
questionnaire. Learning materials used in university student education are also
accessible online. The nature of the new technology interweaves formal and
informal learning such that students can participate actively in the use of ICT
to learn. Otherwise, the teachers will come to a halt a handful of students
behind their students, partially because their particular learning style has not
been triggered without understanding these various learning methods.
Consequently, this survey explored the teachers' understanding of teaching and
their relationship with their engagement to learning. Broadly, the success of
online learning in Malaysia during the COVID-19 Pandemic was determined by the
readiness of technology in line with the national humanist curriculum, support
and collaboration from all stakeholders, including government, schools,
teachers, parents and the community. The findings indicate that students have a
good sense of teaching and there have been strong correlations between the
teacher's perceptions and students' engagement to learning. Teachers are
recommended to consider the nature of the student and to apply appropriate types
of learning tools during their classes. |
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Keywords: |
COVID-19, Education, ICT, Online Learning, University |
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Source: |
Journal of Theoretical and Applied Information Technology
30th June 2021 -- Vol. 99. No. 12 -- 2021 |
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Title: |
HYBRID SOLUTION FOR WIND TURBINES POWER CURVE MODELING FOUNDED ON CASE BASED
REASONING, MULTI-AGENT SYSTEM AND THE K-NEAREST NEIGHBORS ALGORITHM |
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Author: |
MOHAMED KOUISSI, EL MOKHTAR EN-NAIMI, ABDELHAMID ZOUHAIR |
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Abstract: |
The aim of the wind turbines power curve is to represent the performance of a
wind turbine, aids in wind power assessment and also helps in wind power
forecasting. The wind turbines power curve captures the nonlinear relationship
between wind speed and output power. In this paper, we present a hybrid approach
of wind turbines power curve modeling based on Case Based Reasoning approach,
multi agent system and a machine learning algorithm, which is the K-Nearest
Neighbors method to propose a new adapted wind turbines power curve for our
target case based on the wind turbines power curve of similar wind turbines. The
K-Nearest Neighbors algorithm is used in the retrieve step of the case based
reasoning cycle to search for similar wind turbines based on their
characteristics. These wind turbines are then classified and sorted on the basis
of features similarity measure. Then, a new wind turbines power curve of the
target case is proposed based on the experiences of similar cases. |
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Keywords: |
Case Based Reasoning (CBR), Multi Agents System (MAS), Wind Turbines Power Curve
(WTPC), K-Nearest Neighbors algorithm (KNN), Modeling. |
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Source: |
Journal of Theoretical and Applied Information Technology
30th June 2021 -- Vol. 99. No. 12 -- 2021 |
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Title: |
INTERFERENCE AND LOAD BALANCING ROUTING METRICS USED IN WIRELESS MESH NETWORK:
NEW TREND AND CHALLENGES |
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Author: |
BAHAA MUNEER ISMAEL, ASRI BIN NGADI, JOHAN BIN MOHAMAD SHARIF |
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Abstract: |
Wireless Mesh Networks (WMNs) is an integrated concept deployed for the data
communication systems for Internet access. These networks need incorporate and
effective data management, load balancing, interference management and traffic
congestion mechanisms. Data routing in these network by using new and
intelligent routing protocols based on routing metrics play vital role to
increase the network performance. However, the WMN networks have suffered with
load balancing, interference and other routing challenges because only one or
two internet gateways deployed in these networks to access the internet. To
fulfill these network requirements, there is pressing need to design more
efficient routing protocol to deal the WMN networks and provide full network
functionalities. The routing protocols are using different routing metrics or
combination of some routing metrics such as inter-flow interference, hop count
and load balancing for routing decisions. Therefore, a proficient routing metric
is required to make routing protocol more effective. In this paper, we
identified and reviewed many existing routing protocols based on interference,
load balancing and hop count as their routing metrics. We discussed existing
protocols based on their working, metrics and effectiveness. We anticipate that
this research review paper would help the researcher to conduct innovative
research incorporating with the existing routing protocols available in
literature. |
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Keywords: |
Wireless Mesh Network, Routing protocol, Routing Metric, Interference, Load
Balancing |
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Source: |
Journal of Theoretical and Applied Information Technology
30th June 2021 -- Vol. 99. No. 12 -- 2021 |
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Title: |
EXPERT-STATISTICAL METHOD OF MANAGEMENT DECISION SUPPORT FOR AGRICULTURAL
ENTERPRISES OF NORTHERN KAZAKHSTAN |
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Author: |
MAUINA G.M., CHERTKOVA E.A., NUKUSHEVA S.A., AITIMOVA U.ZH., ISMAILOVA A.A. |
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Abstract: |
The article deals with the problem of making management decisions on the
production scenarios of agricultural enterprises in Northern Kazakhstan. The
problem is caused by the presence of a set of criteria (parameters) of
production and market conditions, the correctness of the criteria determines the
quality of making a management decision on the preferred scenario for the
functioning of an agricultural object. The purpose of the study is to structure
the problem and formalize the problem of decision-making on the choice of the
scenario of rational organization of production at the enterprises of the
agricultural sector of Northern Kazakhstan in the conditions of multi-criteria
factors of influence. The research methodology is based on a systematic approach
that allows us to consider a system of interdependent components (resources,
production scenarios) as a closed logical structure that provides rules for
analyzing a complex problem. The heuristic analytical hierarchy process is used
as a mathematical tool of the system approach for solving the multi-criteria
problem of choosing the preferred scenario. The hierarchical approach is
implemented for the decomposition into groups of the considered set of
interdependent components with the procedure of sequential clustering of the
components. Based on this method, the problem of making management decisions on
the scenarios of production of agricultural enterprises is structured in the
form of a dominant hierarchy of four levels. Groups of criteria that
characterize the production conditions of an agricultural enterprise are
identified. To determine the degree of influence (priorities) of the criteria,
it is recommended to introduce expert assessments of the criteria with a
transition from qualitative to quantitative characteristics based on a
verbal-numerical unified scale. The technology for calculating criteria
priorities is based on the matrices of paired comparisons and their
eigenvectors. The practical application of the expert-statistical method based
on the analysis of hierarchies of interdependent criteria allows us to obtain a
management decision on the choice of the optimal production scenario for
agricultural enterprises in Northern Kazakhstan in the conditions of
multi-criteria factors of influence. |
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Keywords: |
Multi-criteria tasks, Analytical hierarchy process, Hierarchy of systems,
Decision-making. |
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Source: |
Journal of Theoretical and Applied Information Technology
30th June 2021 -- Vol. 99. No. 12 -- 2021 |
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