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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
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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 Informtion Technology
November 2021 | Vol. 99
No.21 |
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Title: |
A HYBRID FEATURE SELECTION BASED ADVANCED NEURAL NETWORK OPTIMIZATION MODEL ON
SOMATIC CANCER PREDICTION |
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Author: |
P. R.SUDHA RANI , Dr. K. KIRAN KUMAR |
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Abstract: |
As the size of the micro-array databases and its dimensions are increasing, the
prediction of different gene based disease rules are difficult to handle due to
large features space in the biomedical applications. Micro-array data play
important roles in the different disease pathogenesis. However, experimental
prediction of microRNAs interactions with disease is still difficult. In
addition, some essential limitations of previous computer methods are identified
in the disease network to classify possible interactions of gene-disease. Most
of the conventional feature selection approaches and classification models are
used to predict the gene based patterns on limited dimension space and data
size. In this work, a hybrid feature selection measure is developed to find the
essential key features for the classification problem. In this work, a filter
based feature selection and hybrid classification approaches are implemented on
the high dimensional features. Experimental study show that the present model
has better gene-based pattern extraction efficiency and runtime(ms) than the
conventional models. |
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Keywords: |
Gene Based Micro-Array Dataset, Feature Selection Measures, Gene Classifiction
Disease Prediction. |
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Source: |
Journal of Theoretical and Applied Information Technology
15th November 2021 -- Vol. 99. No. 21 -- 2021 |
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Full
Text |
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Title: |
WAREHOUSE PICKING EFFICIENCY WITH SMART GLASSES (CASE STUDY: XYZ CORPORATE
WAREHOUSE) |
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Author: |
EILEEN HERIYANNI, TEGAR ARYO SULTHON MUSTHOFA, MANISE HENDRAWATY, HIDAYAT
HENDRAKUSUMA |
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Abstract: |
The use of wearable technology devices has been widely used in industry,
especially in the warehouse to carry out the picking process. Picking process
can be interpreted as the process of taking goods according to the specified
location in the warehouse. This research focuses on the application of smart
glasses as wearable devices to increase the efficiency of warehouse picking
process. The implication of this research is to show how wearable devices
provide efficiency during the warehouse picking process and help employees speed
up their work with hands-free atmosphere. |
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Keywords: |
Smart Glasses, Wearable-Device, Android, Warehouse, Warehouse Picking |
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Source: |
Journal of Theoretical and Applied Information Technology
15th November 2021 -- Vol. 99. No. 21 -- 2021 |
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Text |
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Title: |
DIGITAL PLATFORM AS A TOOL FOR INTERNATIONALIZATION: MODEL FOR FORMATION OF
INTERNATIONAL COMPETENCES' DATABASE APPLYING OF HIERARCHY ANALYSIS METHOD |
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Author: |
DAMIRA JANTASSOVA, MURAT KOZHANOV, OLGA SHEBALINA |
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Abstract: |
This research is carried out in the course of the project implementation
"Capacity Building for the internationalization of a technical university by
means of digital learning technologies".
(1) The article considers the issue
of digitalization of the main internationalization processes of a technical
university, describes the developed software application aimed at ensuring the
implementation of internationalization strategies through digital interaction
and the proposed models for assessing key competencies of the educational
program in a synchronous and asynchronous way and the use of the hierarchy
analysis method to select the optimal analysis procedure within the framework of
the section of the information system "Expertise of competencies: an
international base by industry", intended for the formation of an international
base of competencies in conjunction with international experts. |
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Keywords: |
Information System, Competence Base, Internationalization, Hierarchy Analysis
Method, Expertise, Education Program. |
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Source: |
Journal of Theoretical and Applied Information Technology
15th November 2021 -- Vol. 99. No. 21 -- 2021 |
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Title: |
INFORMATION TECHNOLOGY IMPLEMENTATION IN ON-LINE TEACHING AND LEARNING: STAFF
AND STUDENTS ATTITUDE |
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Author: |
LIUDMYLA HOLUBNYCHA, ILONA KOSTIKOVA, YULIIA SYTNYKOVA, TETIANA MELNIKOVA,
NATALIA GUZENKO, ANASTASIIA DOROZHKO |
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Abstract: |
The problem of attitude of teachers and students to on-line teaching and
learning during in and after lockdown is very topical today. The purpose of the
manuscript is to find out and analyze attitude to on-line teaching and learning
in the terms of pandemic 2019–2021. In order to achieve the stated purpose the
following methods were used: empirical (discussion and observation) ones
facilitated distinguishing advantages and challenges that academic staff as well
as university students have faced; research (questionnaires and quantitative
methods) helped to determine the attitude of respondents to the problem under
research. All the surveys were anonymous and conducted on-line. The study was
held in 2019–2021 on the basis of different universities. The target group
became 50 university teachers and almost 200 students of these universities.
In the research we come to the conclusion that at the beginning of the lockdown
in 2019–2020, on-line teaching was a great challenge, especially for university
teachers. They were not ready for on-line teaching as they used to have the
traditional teaching methods with live communication. The low computer and
digital literacy of most teachers was the challenge as well. However, later, in
2020–2021, with teachers’ technical, digital, methodical support for the
teaching process, it became slowly clear that on-line teaching is not temporary
for universities, in the nearest future blended learning will be the basic form.
It has become obvious that on-line teaching expand many educational
opportunities.
As for the students’ opinions, it became clear that they did
not accept on-line learning as tragically as teachers. In 2020–2021 they were
depressed only of the lack of live social life. Later on-line learning required
students to be more self-organized, self-disciplined and self-motivated. The
students realized that they had to take more responsibility for their own
learning results. |
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Keywords: |
On-line, Distance, Teaching, Learning, Technology |
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Source: |
Journal of Theoretical and Applied Information Technology
15th November 2021 -- Vol. 99. No. 21 -- 2021 |
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Title: |
IMPACT OF THE VARIOUS MEASURES OF SIMILARITY ON THE STATISTIC HIERARCHICAL
NEURAL RESPONSE METHOD |
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Author: |
RAMADHAN A. M. ALSAIDI |
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Abstract: |
The neural response is a critical semantic component in the hierarchical
architecture proposed by Smale and known as similarity measures. One standard
measurement used in Smale's framework is the inner product. However, there are
many other measurements such as Dice similarity coefficient, Pearson
correlation, cosine distance, and Euclidean. This work aims to compare and
evaluate which of these similarity measures led to low computational operation
with high accuracy results using Smale framework. The paper introduces a new
approach for selecting an informative and practical template based on
Coefficient of Variation (CV) statistical concept. In this technique, the
developed method reduces the redundancy of the training images and extract
compact template sets with better discrimination ability. The study has shown
that comparing the effectiveness of the Square Pearson correlation (SPCC), Dice
similarity coefficient (DSC), inner product (IP), Euclidean distance (ED), and
chord distance (CD) enables a change in similarity method along with MNIST
database. |
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Keywords: |
Chord Distance, Coefficient of Variation, Cosine Distance, Dice Similarity
Coefficient, Euclidean Distance, Square Pearson Correlation Coefficient,
Statistic Hierarchical Neural Response. |
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Source: |
Journal of Theoretical and Applied Information Technology
15th November 2021 -- Vol. 99. No. 21 -- 2021 |
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Title: |
DIGITAL MARKETING: THE IMPLEMENTATION OF DIGITAL ADVERTISING PREFERENCE AND
DIGITAL CONSUMER NEEDS |
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Author: |
DONI PURNAMA ALAMSYAH, INDRIANA, CHYNTIA IKA RATNAPURI, ERMA LUSIA |
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Abstract: |
The implementation of digital media for marketing is increasing, given its
impact on corporate brands and consumer interest. Digital advertising is used by
the tourism industry with the goal of branding and visiting interest by the
tourism. Based on the phenomenon of the problem, this study aims to examine the
implementation of digital marketing in tourism in supporting consumer brand
awareness and tourism visiting intention. Digital marketing in tourism is
studied from two sides, namely digital consumer needs and digital advertising
preferences. The study was conducted through a survey of 205 consumers in the
city of Bandung (Indonesia) who had received advertising information through
digital marketing. Data from consumers as tourism candidates were obtained
through quantitative questionnaires and processed through SmartPLS to test
research models and research hypotheses. The results of model testing found that
digital advertising preference has a relationship with increasing consumer brand
awareness. Besides that, consumer brand awareness can be a good mediation
between digital consumer needs, digital advertising preferences and tourism
visiting intentions. Directly, tourism visiting intentions can be supported by
digital consumer needs and digital advertising preferences. Finally, a model was
found related to the implementation of digital advertising preferences and
digital consumer needs in supporting consumer brand awareness and tourism
visiting intention. The findings in this study are important information for
marketers in the tourism industry, where the implementation of digital marketing
through advertising and understanding consumer needs provides opportunities for
tourism intention. |
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Keywords: |
Digital Consumer Needs, Digital Advertising Preference, Consumer Brand
Awareness, Tourism Visiting Intention. |
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Source: |
Journal of Theoretical and Applied Information Technology
15th November 2021 -- Vol. 99. No. 21 -- 2021 |
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Text |
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Title: |
AN OPTIMUM LOCATION OF DISTRIBUTED GENERATION FOR SOCIAL SURPLUS MAXIMIZATION IN
SMART GRID WITH INELASTIC LOADS USING BAT ALGORITHM |
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Author: |
RACHAPPA CHIMIRELA, GOPALA RAO JAMMI, VIJAYA KUMAR M |
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Abstract: |
This paper presents the impact of Distribution Generation (DG) on congestion,
loss, Locational Marginal Pricing (LMP), and Social Surplus in the Optimum Power
Flow (OPF) based restructured electricity market. The issue of perfect placement
of DG to reduce congestion and also lower LMPs is formulated with the objective
of social surplus maximization. In this work, the BAT algorithm method by using
DC Optimal Power Flow (DCOPF) is proposed to calculate LMPs at all buses while
maximizing social surplus or minimizing fuel cost. Different scenarios for LMP
determination i.e. not considering losses, losses are considered but
concentrated at reference bus, and losses are distributed at all buses have been
examined. Linear bids are assumed for generators. Here, the load is considered
as fixed i.e. inelastic. The impact of DG on loss, congestion, LMP, and social
surplus has been presented in IEEE 14- Bus system. |
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Keywords: |
BAT Algorithm, DC Optimal Power Flow, Distributed Generation, Electricity
Market, Inelastic load, Locational Marginal Price, and Social Welfare. |
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Source: |
Journal of Theoretical and Applied Information Technology
15th November 2021 -- Vol. 99. No. 21 -- 2021 |
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Text |
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Title: |
THE EFFECTIVENESS FACTORS OF ENTERPRISE ARCHITECTURE INFORMATION SYSTEM
IMPLEMENTATION |
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Author: |
MICHELLE, SFENRIANTO |
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Abstract: |
A research analysis which provides justifiable values from a list of indicators
and factors of the effectiveness of the implementation of the Enterprise
Architecture Information System (EAIS) in State-Owned Enterprise (SOE) and
non-SOE companies which can be validated from a series of validity and
reliability test results using quantitative and qualitative method. Variable
construction was developed through Systematic Literature Research (SLR) and
PRISMA methods. The methodology used using a non-probability method and
purposive sampling technique that was verified by using data sampling resulted
from survey respondents collected through Momentive online questionnaire. The
initial part of this journal describes how key factors before implementing EAIS
could influence the effectiveness of EAIS implementation. The result of this
study will manifest the relation of each of the factors forming the
effectiveness of the EAIS model constitutes the successful EAIS investments at
companies depicted in the Smart-PLS hypothesis relationship result and MaxQDA
code segment system. |
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Keywords: |
Enterprise Architecture, Information Systems, Effective Implementation,
Quantitative, Qualitativ |
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Source: |
Journal of Theoretical and Applied Information Technology
15th November 2021 -- Vol. 99. No. 21 -- 2021 |
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Text |
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Title: |
SOCIAL MEDIA AS A DIGITAL PUBLIC RELATIONS STRATEGY IN MAINTAINING THE IMAGE AND
REPUTATION OF GOVERNMENT INSTITUTIONS |
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Author: |
INDAH AYU PERMATASARI, MUHAMMAD ARAS |
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Abstract: |
This study aims to determine the goals and constraints of public relations for
government agencies in using social media as a digital public strategy.
Meanwhile, the study used a qualitative descriptive approach with a case study
method and data were obtained through in-depth interviews from personnel in the
public relations department of various government institutions. The results
showed that government institutions use social media as a digital public
relations strategy to build positive opinions and the public trust which
maintain the institution's image and reputation. In its management, several
government institutions are constrained by human resources. Meanwhile, the
number of personnel and the ability to present news and creative content become
obstacles to the institutions, therefore, there is a need to cooperate with
external parties. In addition, the content of the information is also an
obstacle because not all news is published through social media. Therefore,
tiered approvals and bureaucracy are conducted to prevent the information
provided from becoming a community controversy. Moreover, the use of social
media has a positive effect on the organization and also poses a risk to damage
the image and reputation of the institution. |
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Keywords: |
Social Media, Communication, Public Relations, Government Institution |
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Source: |
Journal of Theoretical and Applied Information Technology
15th November 2021 -- Vol. 99. No. 21 -- 2021 |
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Text |
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Title: |
SYSTEMATIC LITERATURE REVIEW ON FEATURE RANKING METHODS TO DETERMINE HANDWRITING
RECOGNITION |
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Author: |
NURUL FARAH ATIQAH MOHD TAHIR, INTAN ERMAHANI A. JALIL, MOHD SANUZI AZMI, AZAH
KAMILAH MUDA, SABRINA AHMAD |
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Abstract: |
Features ranking is a very essential step in determining significant features
for handwriting images. Its goal is to increase the classification performance
by reducing the computational cost. In the context of handwriting recognition,
the extraction of image features can lead to the problem of high dimensionality
of data. This has become the handwriting recognition problem whereby the
variation of generated features are contributing to the factor of irrelevant or
redundant features while maybe even correlated to each other that burden the
classification process. As a result, this will be contributing to the lower
identification performance accuracy due to the increase of computational
complexity. This paper used a Systematic Literature Review (SLR) to compile the
features ranking based technique to overcome the drawbacks above. SLR is a
literature review that collects and critically analyzes multiple studies to
answer the research question. Five research questions were drawn for this
purpose. Information such as techniques, collection of datasets and methods’
performances were extracted from 52 articles. This information was analyzed to
identify the strengths and weaknesses of the techniques and the affecting
elements to the performance of features ranking. The SLR has also found out that
some of the studies were using feature selection methods in handwriting
recognition. The efficiency of some feature selection methods has exceeded other
approaches, even though it is only at a reasonable level. Therefore, more
studies are needed to overcome the drawbacks of the handwriting recognition by
using features ranking. |
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Keywords: |
Feature Extraction, Features Ranking, Feature Selection, Handwriting Recognition |
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Source: |
Journal of Theoretical and Applied Information Technology
15th November 2021 -- Vol. 99. No. 21 -- 2021 |
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Text |
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Title: |
COMPETITIVE CANDIDATE DETERMINATION SYSTEM FOR STUDENTS WITH COMPARATIVE
ANALYSIS OF WEIGHTED PRODUCT (WP) ALGORITHM AND TECHNIQUE FOR ORDER BY
SIMILARITY (TOPSIS) |
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Author: |
HANDRIZAL, ELVIWANI, M ARIF KURNIAWAN |
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Abstract: |
The competition will be one of the indicators that make a university at its
best. The more students who take part in competitions will certainly have a
positive impact on the university itself. The achievements and victories
achieved by students are interpreted as a form of university success in
educating students both in terms of theory and practical skills. The track
record of student achievement will always make the accreditation of a university
even better because it presents graduates who are competent in their fields. The
selection process will be something that needs to be done considering that many
criteria must be met by the student before being declared ready to compete for
both in theory and practice so that a decision support system is needed that can
provide recommendations for student choices. This research will discuss the
process of determining the candidate for the race by analyzing two methods,
namely the Weighted Product (WP) method and the Technique for Order by
Similarity to Ideal Solution (TOPSIS) method in which the two methods will
analyze what percentage of the resulting level of accuracy is the output on the
system is the same as the manual calculation. Furthermore, the writer will also
analyze how far the difference is between the two methods using Euclidean
Distance and the weighting of the criteria using a Likert Scale. The results of
the comparative analysis show that the WP method is the best method with a value
of 0.14281 because it has a value close to zero compared to the TOPSIS method
with a value of 0.51238 even though both produce the same level of accuracy
reaching 100%, but the WP method is still more optimal in terms of program
execution speed (Micro time) with an average time of 0.0781 seconds while the
TOPSIS method takes an average of 0.2234 seconds |
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Keywords: |
Decision Support System, Candidate Participants, Likert Scale, Weighted Product,
Technique for Order by Similarity to Ideal Solution, Euclidean Distance |
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Source: |
Journal of Theoretical and Applied Information Technology
15th November 2021 -- Vol. 99. No. 21 -- 2021 |
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Text |
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Title: |
AN EFFICIENT NONLINEAR ACCESS POLICY BASED ON QUADRATIC RESIDUE FOR CIPHERTEXT
POLICY ATTRIBUTE BASED ENCRYPTION |
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Author: |
ANCY P R , ADDAPALLI V N KRISHNA |
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Abstract: |
Ciphertext Policy Attribute Based Encryption (CP-ABE) is an efficient encryption
scheme as data owner is making decision about the attributes that can access his
data and adding that attributes to access structure while encrypting that
message. Most existing CP-ABE scheme are based traditional access structure such
as linear secret sharing scheme which incur large ciphertext size and linearly
increases according to the number of attributes. And those schemes have more
computational overhead for calculating share for each attribute and when
recalculating secret in data user side. In this paper, we propose a different
secret sharing scheme that can be used in access policy for CP-ABE which will
reduce the size of ciphertext and there by communication overhead. Furthermore,
the proposed scheme reduced computational overhead of secret sharing scheme and
improved overall efficiency of the scheme. |
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Keywords: |
Ciphertext Policy Attribute Based Encryption, Access Policy, Non-linear Secret-
Sharing Scheme, Encryption, Quadratic Residue |
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Source: |
Journal of Theoretical and Applied Information Technology
15th November 2021 -- Vol. 99. No. 21 -- 2021 |
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Full
Text |
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Title: |
A DISCRIMINANT ANALYSIS OF ACTUAL USE OF CLOUD TECHNOLOGY FOR VOCATIONAL AND
TECHNICAL EDUCATION |
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Author: |
SATHAPORN YOOSOMBOON, THANYATORN AMORNKITPINYO, SUNTI SOPAPRADIT, PIMPRAPA
AMORNKITPINYO, RAVIWAN KINHOM |
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Abstract: |
The objectives of this research are 1) to study the independent variables that
are used in the stepwise discriminant analysis of the actual use of cloud
technology, 2) to create a discriminant function of the actual use of cloud
technology. The sample consists of 1,620 Thai vocational and technical students
who have used cloud technology. The data collection tool used in this study is a
questionnaire. The statistical analysis used in this research is ‘Stepwise
Discriminant Analysis (SDA)’. The results indicate that 1) the t-test results
with regard to seven independent variables (Perceived Usefulness, Perceived Ease
of Use, System Quality, Information Quality, Service Quality, Perceived
Security, and Social Cloud) were at a significance level of .05. This could be
used to classify the groups in terms of ‘Actual Use of Cloud Technology’, and 2)
the accuracy of the set of these seven variables that were used to predict the 3
groups was at 88.1 percent. |
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Keywords: |
Technology Acceptance Model, Social Cloud, Information System Success Model,
Perceived Security. |
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Source: |
Journal of Theoretical and Applied Information Technology
15th November 2021 -- Vol. 99. No. 21 -- 2021 |
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Title: |
TOWARDS THE ADOPTION OF DRONES IN FOODSERVICE INDUSTRY: A GENERIC MODEL
DEVELOPMENT |
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Author: |
NOOR ISLAM JASIM, HAIROLADENAN KASIM, MOAMIN A. MAHMOUD |
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Abstract: |
Drone technologies have recently received a great deal of attention due to their
high mobility, low cost, and flexible deployment. It is anticipated that drones
will be part of our daily life, just like smartphones. The wide deployment of
drones in different domains such as healthcare, agriculture, traffic monitoring,
firefighting, national defense, rescue activity, and delivery services such as
food and retail. Drones are expected to have a significant contribution to food
delivery services by saving time, cost, environment, and people's life by
reducing traffic congestion, wages, carbon emission, and accidents,
respectively. Recently, big corporations, such as Amazon and DHL, have deployed
drones as an alternative to traditional delivery methods. However, service
providers of drone food delivery (DFD) services need to identify significant
factors that influence potential consumers' to use drone delivery. Existing
models lack a comprehensive basic theory that addresses factors that influence
consumers' intention and behavior. To overcome this limitation and propose a
more comprehensive model, relevant research studies from the domain of drone
delivery services and other emerging technology such as IoT, Autonomous
Vehicles, and Mobile Banking are identified, reviewed, analyzed, and ten
potential factors are subsequently extracted. The model is expected to inspire
food-service sub-sectors in planning for the adoption of drone technology
adoption in evaluating an existing DFD or developing a new one. |
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Keywords: |
Drone, Food Delivery, Generic Model, Acceptance Model |
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Source: |
Journal of Theoretical and Applied Information Technology
15th November 2021 -- Vol. 99. No. 21 -- 2021 |
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Full
Text |
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Title: |
IMPACT OF DISTRIBUTED GENERATION IN SMART GRID ON SOCIAL SURPLUS AND LOCATIONAL
MARGINAL PRICE IN DEREGULATED POWER MARKET WITH ELASTIC LOADS |
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Author: |
RACHAPPA CHIMIRELA, GOPALA RAO JAMMI, VIJAYA KUMAR M |
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Abstract: |
This paper presents the impact of Distribution Generation (DG) on congestion,
loss, Locational Marginal Pricing (LMP), and Social Surplus in the Optimum Power
Flow (OPF) based restructured electricity market. The issue of perfect placement
of DG to reduce congestion and also lower LMPs is formulated with the objective
of social surplus maximization. In this work, the BAT algorithm method by using
DC Optimal Power Flow (DCOPF) is proposed to calculate LMPs at all buses while
maximizing social surplus or minimizing fuel cost. Different scenarios for LMP
determination i.e. not considering losses, losses are considered but
concentrated at reference bus, and losses are distributed at all buses have been
examined. Linear bids are assumed for generators. Here, the load is considered
as elastic. The impact of DG on loss, congestion, LMP, and social surplus has
been presented in IEEE 14- Bus system. |
|
Keywords: |
BAT Algorithm, DC Optimal Power Flow, Distributed Generation, Electricity
Market, Locational Marginal Pricing, and Social Welfare. |
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Source: |
Journal of Theoretical and Applied Information Technology
15th November 2021 -- Vol. 99. No. 21 -- 2021 |
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Full
Text |
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Title: |
IMAGE ENHANCEMENT BASED ON NONLINEAR AND ANISOTROPIC DIFFUSION |
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Author: |
MOHAMMED AIT OUSSOUS, YOUSSEF AIT KHOUYA |
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Abstract: |
In this paper, we present evidence of the existence and the uniqueness of the
solution of the proposed model in [1], where is applied to image enhancement and
filtering. The main idea of the model is to apply a Gaussian filter to the image
gradient when computing the diffusion coefficient. The gradient threshold
parameter is also calculated from the image gradient at each iteration. The
numerical experiments are presented along with a discussion of results. |
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Keywords: |
Nonlinear Reaction- Diffusion, Image Processing, Gaussian Filter, Image
Gradient, Existence and and Uniqueness. |
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Source: |
Journal of Theoretical and Applied Information Technology
15th November 2021 -- Vol. 99. No. 21 -- 2021 |
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Title: |
BUSINESS PROCESS VERIFICATION WITH INTEGRATED SIMULATION METHODS: FOCUS ON
"CUSTOMER ENGAGEMENT» |
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Author: |
SALIMA ISRAILOVA, AYAGOZ MUKHANOVA, TATYANA YESIKOVA, MERUYERT KOISHYBAYEVA |
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Abstract: |
Many business process-modeling techniques cover and address various aspects of
the business process. A limited number of these process models allows further
quantitative analysis, and only a few allow structuring the process. This
article discusses and classifies the main methods of modeling business processes
from the view of their analysis and the possibilities of optimizing the business
process taking into account the client's attracting. There are three types of
methods, on the basis of which the choice of representative methods of business
process modeling is classified. A similar classification is presented for the
approaches of analysis and optimization of business processes identified in the
relevant literature. The main contribution of the article is that it determines
which business process methods are suitable for analysis and optimization, and
also it highlights the disadvantages of such approaches. This article presents a
modern review in the field of modeling, analysis and optimization of business
processes with the emphasis on the ways to attract customers, which have not
received sufficient coverage and support in the literature of post-Soviet
countries. Organizations can make a big profit for themselves by having a
documented business process model available. This gives it’s activities greater
transparency, which in turn is an additional stimulating factor of investment
attractiveness for the organization. For developing companies seeking to ensure
competition in the market, it is especially important to have a clear
understanding of the role of business process modeling and its necessity, and
its place in the organization. Today, most organizations are actively trying to
create their own models business processes or use existing models, and there is
a reason for this their reasons, which can be easily explained by various
factors. |
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Keywords: |
Business-Process (BP), BP Analysis, Petri Nets, BP Modeling, BP Optimization,
Simulation Methods. |
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Source: |
Journal of Theoretical and Applied Information Technology
15th November 2021 -- Vol. 99. No. 21 -- 2021 |
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Text |
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Title: |
DIAGNOSTIC OF INTEGRATED DATA MANAGEMENT FOR FINANCIAL SERVICE REGULATORY AND
SUPERVISORY, CASE STUDY: INDONESIA |
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Author: |
WIRIANTO WIDJAYA, RENDY DALIMUNTHE, INDRAJANI SUTEDJA, ARMAND WAHYUDI HARTONO |
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Abstract: |
The progression of the digital revolution has changed the business landscape
everywhere, including for Financial Service Industry (FSI). The use of
technology improves the overall effectiveness and efficiencies of business
operations. Aside from its benefit, the use of technology also introduces new
types of risk. This condition forces the FSI regulatory and supervisory agencies
or Financial Service Authority (FSA) to find new ways to handle it while
harvesting the benefit.
In this context, FSA should effectively use the
collected data to monitor and supervise the FSI's health, business conduct, and
compliance with regulations. To achieve this objective, FSA should be able to
manage the data through its entire cycle. Data management is a complex process
in nature. In many cases, organizations need to figure out where to start with
the initiatives.
This study aims to identify the main requirements and
challenges in Data Management for FSA in the Indonesian context. It uses the
Architecture Development Method (ADM) to guide the process and refers to DAMA
Framework as the foundation for analysis. The study concludes that FSA needs to
develop a data and information strategy, understand the overall data and
information requirement, design their enterprise data architecture, and use the
proper technology to address various challenges and needs in the data and
information management context. The FSI’s Integrated Data Management
Architecture (IDMA) is required to address these needs. Data Management
initiatives are a critical and foundational factor for FSA to successfully
promoting stable and sustainable growth of FSI in the ongoing digital revolution
era. A similar organization could use the output of this study as a reference to
map the current condition of data management and provides essential input for
the preparation of organization-wide data management framework implementation. |
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Keywords: |
Diagnostic Study, Data Management, Financial Service Authorities, Indonesia |
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Source: |
Journal of Theoretical and Applied Information Technology
15th November 2021 -- Vol. 99. No. 21 -- 2021 |
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Title: |
LOCATION SELECTION FOR A TEXTILE MANUFACTURING FACILITY USING NEURAL
NETWORK |
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Author: |
ABDERAHMANE FARHATE, RAJA ELBOQ, SAMIR TETOUANI, AZIZ SOULHI |
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Abstract: |
The location selection of a textile manufacturing facility is a crucial decision
that could reconfiguration the economic map of any city. This selection of
textile industrial zones is based on a set of criteria such as the proximity of
the market, the suppliers and the logistical costs involved due to the chosen
location and this in an ecosystem that must offer the most favorable conditions.
Even though it is a very important decision, there are very few studies on the
location selection of the textile manufacturing facility within the Moroccan
context. A Neural Network Model (NNM) was developed to rank suitable areas for a
textile manufacturing facility in Morocco.
The data used in this study are as
follow; Surface Area, Location and general infrastructure, Internal equipment,
Urban planning prescriptions, Price, Occupancy, Population, Taxation, Means of
communications.
Then, according to the case study presented in this paper,
which is based on the developed NNM, the area of SETTAT was determined as the
most suitable area for the establishment of a textile manufacturing facility in
Morocco.
This study aims to make two contributions to the literature.
Firstly, to fill the research gap in one of the most attractive countries for
the establishment of an industrial facility, and more specifically a textile
facility. Then, a robust decision and prediction model is used to select the
most appropriate location |
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Keywords: |
Industrial Areas, Localization, Selection, Neural network |
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Journal of Theoretical and Applied Information Technology
15th November 2021 -- Vol. 99. No. 21 -- 2021 |
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Title: |
THE USE OF GAMIFICATION TO IMPROVE KNOWLEDGE SHARING PROCESS IN AN UTILITY
COMPANY by USING ARCS MODEL: CASE STUDY IN AN UTILITY COMPANY |
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Author: |
VIAN ENDRAMANTO, GUNAWAN WANG , VIANY UTAMI TJHIN |
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Abstract: |
Knowledge is neither data nor information, but knowledge cannot exist without
data and information. To manage a collection of knowledge on an ongoing basis, a
Knowledge Management System (KMS) is required which is created to manage
knowledge electronically and can be accessed by all employees so as to
facilitate the knowledge creation process. PT PLN (Persero) has KMS to manage
the knowledge creation process, one of which is in terms of knowledge sharing
(KS) activities. Gamification can be used to motivate employees to participate
in the knowledge creation process, especially in knowledge sharing, so that it
can encourage the creation of new knowledge that can encourage the creation of
new innovations for PT PLN (Persero). Motivational design ARCS model and MDA
framework are used as the basis for the design of the user interface
gamification in PT PLN (Persero) knowledge creation process so that it can
provide a gamification system that can motivate employees' desire to share
knowledge at PT PT PLN (Persero). |
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Keywords: |
Gamification, User Interface Design, Knowledge Management System, Knowledge
Creation, Knowledge Sharing, ARCS Model, MDA Framework. |
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Journal of Theoretical and Applied Information Technology
15th November 2021 -- Vol. 99. No. 21 -- 2021 |
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Title: |
TOWARDS A CONTEXT-DRIVEN TRANSACTIONAL SERVICE SELECTION MECHANISM IN UBIQUITOUS
AND PERVASIVE ENVIRONMENTS |
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Author: |
ETTAZI WIDAD, RIANE DRISS, NASSAR MAHMOUD |
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Abstract: |
Most prominent techniques and selection algorithms only support QoS settings for
application services. However, the software, hardware, and network
infrastructures underlying services and users application have a significant
impact on the validation of transactional services. Additionally, users may have
varying transactional requirements throughout the lifecycle of a service
composition. Therefore, selection algorithms must take into account the context
requirements and users transactional needs when selecting services. This has led
us to explore the trail of a service selection mechanism based on a service
description enriched by functional and transactional requirements, and context
information. We propose a context-driven selection of transactional services by
introducing a new selection algorithm CT2S based on a semantic matching
mechanism. More precisely, we are interested in studying the response time of
our CT2S algorithm vis-a-vis the rapidity requirements in pervasive
environments. |
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Keywords: |
Context-Awareness, Transactional Service, Semantic Matching, Selection
Mechanism, Service Discovery. |
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Journal of Theoretical and Applied Information Technology
15th November 2021 -- Vol. 99. No. 21 -- 2021 |
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Title: |
MEASURING IMPACT OF UNIVERSITY RESEARCH GRANT: A SYSTEMATIC LITERATURE REVIEW |
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Author: |
NUR AZURA SANUSI, NOOR HAYATI AKMA SHAFIEE, NOR ERMAWATI HUSSAIN, ZUHA ROSUFILA
ABU HASAN, MOHD LAZIM ABDULLAH, NOR HAYATI SAAT |
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Abstract: |
Currently, there is an increasing concern on government funding on research in
the education field. In general, research is an essential field for any public
and private educational institutions. Research also provides a significant
impact to increase the country’s productivity, thus boosting its reputation
globally. The main issue is how research grants funded by government can provide
returns towards academicians, society, and the country. Thus, the objectives of
this study was to identify indicators to measure impact of the university
research grant. The systematic review of the literature method was conducted
using two main journal indexed databases: Web of Science (WoS) and Scopus. From
the analysis, the results showed that four themes and 24 sub-themes were
connected to the research impact. The four themes were scholarly production
impact (10 sub-themes), research advancement impact (8 sub-themes), policy
implication (3 sub-themes), and health and economic impact (3 sub-themes), which
were discussed in the results. In conclusion, investment in research is
important to help various parties gain benefits as listed in the research
advancement impact theme of this study. |
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Keywords: |
Output, Outcome, Impact, University Grant, Systematic Literature Review |
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Journal of Theoretical and Applied Information Technology
15th November 2021 -- Vol. 99. No. 21 -- 2021 |
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Title: |
THE CLASSIFICATION OF POSSIBLE CORONAVIRUS TREATMENTS ON A SINGLE HUMAN CELL
USING DEEP LEARNING AND MACHINE LEARNING APPROACHES |
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Author: |
NOUR ELDEEN KHALIFA, GUNASEKARAN MANOGARAN, MOHAMED HAMED N. TAHA, MOHAMED LOEY |
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Abstract: |
Every major healthcare system is now under the throes of the Coronavirus disease
outbreak as it is operating at its maximum capacity. There is an absolute need
to establish an appropriate cure for this virus as quickly and efficiently as
possible. Advances in deep learning models may play a critical role in SARS-2
discovery by locating a possible treatment. This article's objective is to
demonstrate the machine learning and deep learning models approaches for
classifying prospective coronavirus treatment on a single human cell. A partial
dataset of RXRX.ai which is a publicly available dataset is used in this
research. This work targeted to implement a strategy for automatically
identifying a single human cell depending on the type of treatment and its
concentration level. Throughout this study, we present a DCNN model along with
an image processing approach. The systematic approach comprises translating the
original dataset's numerical attributes to the image domain, and then
incorporating them into DCNN model. In comparison to standard machine learning
techniques including such Ensemble, Decision Tree and Support Vector Machine,
the experimental findings indicate that the suggested DCNN model for treatment
classification (32 categories) obtained a testing accuracy of 98.05 percent. The
(Ensemble) algorithm achieves 98.5 percent for the accuracy test in treatment
concentration level prognosis, whereas the suggested DCNN model reached 98.2
percent. The classification of treatments and assessing their concentration
levels are considerably accurate due to the performance indicators obtained from
the experiments. |
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Keywords: |
Deep Learning; Machine Learning; Coronavirus, COVID-19 |
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Journal of Theoretical and Applied Information Technology
15th November 2021 -- Vol. 99. No. 21 -- 2021 |
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Title: |
GENERATION OF COMBINATORIAL LOGIC ORIENTED TEST CASES FROM UML SEQUENCE DIAGRAM |
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Author: |
SUBHASH TATALE, Dr. V. CHANDRA PRAKASH |
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Abstract: |
In the current practice, the test cases are generated from UML artefacts
depending on the experience of testers in testing. Many researchers used
different techniques to generate test cases from UML artefacts. There is a need
to generate combinatorial logic-oriented test cases for those systems where
combinatorial logic is necessary.
Combinatorial testing plays an essential
role in generating a minimum number of the test cases to detect defects caused
by interactions among system parameters. To generate combinatorial
logic-oriented test cases, information about parameters, their values, and
constraints is essential.
UML Sequence Diagram represents the dynamic
behaviour of a software system. Extracting and identifying information about
parameters, values and constraints from UML Sequence Diagram and detecting
interactions among those extracted parameters is challenging task. The authors
proposed multi-stage algorithm to extract and identify information about
parameters, values and constraints from Sequence Diagram. The authors designed
and developed a technique that automatically generates combinatorial
logic-oriented test cases from UML Sequence Diagram.
In this paper, a case
study of Concession Management SubSytsem of Indian Railways is presented. The
authors generated automated test cases using the proposed Combinatorial Logic
Oriented Test Case Generator for the case study and compared those test cases
with manually generated test cases. It is found that generated automated and
manual test cases are matching the same with each other. |
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Keywords: |
Covering Array, Combinatorial Test Case Generation, Behavioral UML Diagrams,
Sequence Diagram, Railway Reservation System, Concession Management System |
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Source: |
Journal of Theoretical and Applied Information Technology
15th November 2021 -- Vol. 99. No. 21 -- 2021 |
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Title: |
FACE RECOGNITION TECHNIQUES : A SYSTEMATIC LITERATURE REVIEW (RESEARCH TRENDS,
DATASETS, AND METHODS) |
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Author: |
DIAN ADE KURNIA , OTHMAN MOHD, FAIZAL ABDOLLAH, DADANG SUDRAJAT, YUDHISTIRA ARIE
WIJAYA |
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Abstract: |
Recent research on face recognition techniques typically results in datasets and
methods that enable image processing to concentrate on image quality
development. Numerous datasets and methods for face recognition techniques are
published in disparate and complex formats, and thus a comprehensive overview of
the current state of face recognition techniques research is missing. The
objective of this literature review is to identify and analyze the research
trends, datasets, and methods used in research on face recognition techniques
between 2015 and 2020. The systematic literature review (SLR) approach was used
to conduct this review of the literature. A systematic review of the literature
is defined as the process of identifying, evaluating and interpreting all
available research evidence to elucidate specific research questions. The steps
are to ascertain what SLR requires, develop a review protocol, conduct a search
for primary studies, select primary studies, extract data from primary studies,
assess primary studies, analyze data from primary studies, and synthesize data
from primary studies. 28 face recognition techniques studies published between
2015 and 2020 were retained and further investigated based on the defined
inclusion and exclusion criteria. According to the analysis of the primary
studies, current face recognition research focuses on six methods or techniques:
PCA, CNN, SVM, Gabor, HOG, and LBP. The six most frequently used classification
techniques in face recognition account for 25% of all techniques: PCA, 20% of
Gabor, 20% of SVM, 15% of CNN, 10% of LBP, and 10% of HOG. Additionally, 78% of
research studies analyzed public datasets, while 22% analyzed private datasets.
This essay is structured as follows. Section 1 contains an introduction to the
research and research’s problem, research objective and problem statement.
Section 2 contains the research methods using Systematic Literature Review, and
Section 3 discusses the Results and Finding. Section 4 contains the Conclusion |
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Keywords: |
SLR, Face Recognition Techniques, Primary Studies, Synthesize |
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Source: |
Journal of Theoretical and Applied Information Technology
15th November 2021 -- Vol. 99. No. 21 -- 2021 |
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