		FeedBack \| Contact Us \| Links \| Site Map

Welcome to Journal of Theoretical and Applied Information Technology

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).

Journal of Theoretical and Applied Information Technology

July 2023 | Vol. 101 No.14

Title:	SENTIMEN ANALYSIS ON THE NEW VARIANT OF COVID-19 (OMICRON) IN INDONESIA USING BERT TEXT REPRESENTATION
Author:	DAMAR LAZUARDI S PUTRA, TUGA MAURITSUS
Abstract:	The number of opinions that appear can give rise to many perceptions, it is difficult to know the tendency of opinions from the many comments, not only positive perceptions but also negative perceptions including opinions regarding the emergence of a new variant of the Coronavirus. The number of new variants ranging from Alpha to Omicron has resulted in a decrease to an increase in COVID-19 cases, which requires the government to make various policy strategies. All forms of policy changes and these conditions create uncertainty that makes people feel afraid and worried about uncertain conditions. The purpose of conducting a sentiment analysis is to find out public opinion regarding the new variant of Covid-19 more generally and to determine the level of accuracy obtained using the BERT text representation, the CRISP-DM framework and the Naive Bayes method. The result of this sentiment analysis is that the perception of the Indonesian people towards the new variant of Covid-19 (omicron) tends to be neutral with a percentage of 27,65 (553), followed by a negative percentage of 7,6% (7,6), and a positive percentage of 64,75% (1295) from 2000 tweet data. From the results of testing the accuracy values obtained by BERT and the Naive Bayes model regarding the perception of the Indonesian people towards the new variant of Covid-19 (omicron) with a comparison of training data and test data in testing using a confusion matrix with both training data and test data comparisons being 80:20 get 77% accuracy for Naive Bayes, 82% accuracy for Support Vector Machine, and 90% accuracy for Random Forest.
Keywords:	Omnicron, Bert, Naive Bayes, Support Vector Machine, Random Forest, Sentiment Analysis.
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	A NOVEL HYBRID INTRUSION DETECTION MODEL FOR INTERNET OF THINGS USING MACHINE LEARNING
Author:	L. SARALADEVE, A. CHANDRASEKAR
Abstract:	The identification of attacks in the infrastructure of the Internet of Things (IoT) is becoming a progressive problem in the field of IoTs. The proliferation of IoT infrastructures across all domains has coincided with an increase in the number of attacks and threats. To address this issue, a new hybrid intrusions detection system (IDS) model is developed in this paper for attacks detection and classification. The proposed model is a combination of a metaheuristic algorithm and a machine learning technique. The metaheuristic algorithm called Binary Enhanced-Whale Optimization Algorithm (BEWOA) is used for the selection of features and the machine learning algorithm called Random Nearest Neighbor (r-NN) is utilized for the classification. This BEWOA-rNN model is evaluated using the NSL-KDD and UNSW-NB-15 datasets. The workflow of the model includes the preprocessing, dataset splitting, feature selection and classification. Using the normalization technique, the preprocessing process is performed for data standardization and data cleaning. After preprocessing, the features from the datasets are selected using the BEWOA algorithm for improving the classification performance of the model. Based on the selected features the classification is performed and the performance is measured in terms of detection rate, accuracy, specificity, f-measure, and precision. The performance evaluation is measured individually for both the datasets using the BEWOA-rNN model. The model obtained 99.22% accuracy, 98.82% detection rate, 99.63% specificity, 99.64% precision, and 99.23% f-measure using the NSL-KDD dataset. The model obtained 99.06% accuracy, 98.90% detection rate, 99.22% specificity, 99.24% precision, and 99.07% f-measure using the UNSW-NB-15 dataset.
Keywords:	IoT, Attack Detection, IDS, BEWOA, r-NN, Machine Learning.
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	BLOCKCHAIN SYSTEM APPLICATION IN INSURANCE FOR MAPPING HEALTH INFORMATION SYSTEM
Author:	FALDI , KHALISH ARSY AL KHAIRY SIREGAR , HASYRUL HAMZAH , RAHMAN ANSHARI , BAMBANG SETIAJI , JATI PRATIWI , ERIKA NANDINI , RIZKY KURNIAWAN SYAMAT
Abstract:	Indonesias population density is an issue, one of which is the significance of a health system that can assure the sustainability of people's lives in Indonesia. The value of insurance is an important asset that every Indonesian citizen must have in this study utilizing the SLR (systematic literature review) approach with descriptive analysis based on research data. The search parameters include articles from 2010 to 2021, and the articles are sorted based on those that satisfy the requirements. The primary material of each article is summarized using a descriptive analysis model and paragraphs. This study found 31 papers that met the requirements. Blockchain is a decentralized system with no centralization that uses connections to provide transparency and real-time. This technology allows apps to keep and share a safe, transparent, and immutable audit trail while minimizing red tape. However, this approach has significant limits and obstacles that must be addressed in future studies.
Keywords:	Blockchain, Health Insurance, Health Information System, Insurance Management, Indonesia's National Health Insurance
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	ENHANCING BREAST CANCER PREDICTION THROUGH HYPERPARAMETER OPTIMIZATION IN SUPPORT VECTOR MACHINE
Author:	VERONICA LANDREA DARNELLA OSWARI, RAYMOND SUNARDI OETAMA
Abstract:	Breast cancer is a prevalent and serious disease in the United States, ranking as the third leading cause of death worldwide. The number of cancer-related deaths has risen from 6.2 million in 2000 to 10 million in 2020. Early detection is vital for saving lives and improving treatment outcomes. While the accuracy rate in breast cancer prediction has reached around 97%, other research in different healthcare fields has achieved even higher accuracy rates ranging from 98.062% to 100%. To advance the field and enhance the accuracy of breast cancer detection methods, this study investigates and optimizes previously unexplored parameters. One approach involves utilizing data mining techniques, specifically by combining the Support Vector Machine (SVM) algorithm with Linear Kernel, RBF Kernel, and tuning hyperparameters. The Linear SVM model exhibited exceptional performance, accurately predicting most Malignant and Benign instances with only two incorrect predictions. The SVM model with the RBF kernel demonstrated comparable performance, with minimal errors. By tuning the hyperparameters and utilizing the RBF kernel, the SVM model achieved perfect predictions for Benign cases and high accuracy for Malignant cases. Both the Linear SVM and H-SVM models achieved the highest accuracy of 98.83%, with the RBF SVM model close behind at 98.24%.
Keywords:	Breast Cancer, Data Mining, Early Detection, SVM algorithm.
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	STUDY OF OPEN INNOVATION AND INTELLECTUAL PROPERTY EFFECT ON FIRM PROFIT IN THE FRAME DUOPOLISTIC MARKETS
Author:	ELMIRE AZIZ, AIT BASSOU AZIZ, HLAYAL MUSTAPHA , EL ALAMI JAMILA
Abstract:	In this research paper, we will probe the influence of open, closed innovation and intellectual property rights protection on competitive advantage by implementing the Cournot duopoly model. The study is set up in two phases: firstly, assessing the effects of the open innovation strategy rate on the competitive landscape, and secondly, proposing a novel model for intellectual property profit based on exponential function. The findings have indicated that embracing open innovation can result in greater profits and market share for both firms, exceeding the outcomes of closed innovation approaches. Also, we demonstrated that they are a link between the open innovation adoption and intellectual property. These results carry important implications for companies operating in innovation-intensive sectors and emphasize the potential advantages of adopting collaborative innovation strategies.
Keywords:	Open innovation; Close innovation; Duopoly market; Games theory.
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	INNOVATION DIFUSSION MODEL IN AUDITORS’ ACCEPTANCE OF METAVERSE TECHNOLOGY
Author:	PBAMBANG LEO HANDOKO, PANG SWAT LIN LINDAWATI, PHARYADI SARJONO, PMAZLINA MUSTAPHA
Abstract:	Technological developments in the current industry 4.0 era have provided many rapid changes, including the metaverse technology that uses virtual reality. This technology metaverse has also penetrated the world of auditing. Many digital assets, including virtual assets in the metaverse, must also be audited. it requires auditors to master metaverse technology. This is what made us compile research on the factors that influence auditors' intention in accepting the metaverse technology from the point of view of innovation diffusion theory. The contribution of research in the IT field is to provide an overview of the use of information technology, especially in the metaverse field that is applied in the auditing field. Our research is a quantitative study, we use primary data obtained from distributing e-questionnaires to auditors who work in public accounting firms. We performed data analysis using the structural equation modeling partial least square method. The results of our study state that trialability, observability and user compatibility have a significant effect on auditors' intention to accept metaverse technology, while the other two variables, namely complexity and relative advantage, have no significant effect.
Keywords:	64TMetaverse, Technology, Auditor, Innovation, Diffusion, Theory
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	A NOVEL METHOD TO ENHANCE THE RELIABILITY OF TRANSMISSION OVER SECURED SDWAN OVERLAY
Author:	MOHIT CHANDRA SAXENA, MUNISH SABHARWAL, PREETI BAJAJ
Abstract:	The secure transmission of data over Software-Defined Wide Area Network (SDWAN) overlays is of paramount importance in today's interconnected world. However, ensuring both security and reliability poses significant challenges. In this research paper, we propose a novel method to enhance the reliability of transmission over secured SDWAN overlays. Our approach leverages advanced encryption and authentication techniques to secure the data transmission, while also incorporating best in class Reed Solomon FEC encoding, which perform very well in lossy network conditions. By considering factors such as link quality, latency, and packet loss, our method optimizes the transmission reliability for both TCP and UDP traffic at a minimal overhead. Through extensive simulations and evaluations, we demonstrate the effectiveness of our proposed method in enhancing transmission reliability. The results reveal significant improvements in packet delivery ratio, reduced packet loss and latency, and enhanced overall network performance compared to traditional SDWAN solutions. The findings of this research have implications for various industries, including finance, healthcare, and critical infrastructure, where secure and reliable data transmission is essential. Our novel method contributes to the advancement of SDWAN technology by addressing the critical challenge of maintaining reliability without compromising security.
Keywords:	IP Transport, networking, security, cybersecurity, SDWAN, FEC, TCP, UDP, Packet Loss, link performance, Overlay, underlay, VPN, Network-Security, IPSEC, smart WAN
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	TOWARDS SOCIAL JUSTICE VIA GIVING: AGENT-BASED ECONOPHYSICS MODELS OF TAXATION AND ZAKAT
Author:	ERŞAN TAŞAN, BERTAN BADUR
Abstract:	Growing inequality in modern capitalist economies is a major problem. Throughout human history, compulsory giving (taxation) and voluntary giving (almsgiving) have been utilised to ameliorate inequality and its harmful effects. In this study, we build an agent-based model of an artificial transaction economy benefitting from the ideas of econophysics literature. In this simple economy, the only interaction is money transfer among agents, which can be likened to thermal interaction among gas molecules. This results in an exponential wealth distribution, which is an indicator of severe inequality. We examine the effectiveness of taxation policy and almsgiving (particularly Islamic practice of zakat) on reducing inequality of wealth distribution via simulation experiments. Our results demonstrate that both of these practices engender a fairer redistribution of wealth. This contributes to econophysics literature via showing that inequality arising from fixed money transfers can be reduced through giving behaviour of agents. Furthermore, zakat, if practised by every member of society, helps with social justice even if target recipients are chosen randomly, not necessitating for targeting the poorest. In addition, we find optimum values for giving out of wealth (around 7.5% of wealth after every transaction in our model conditions), above which inequality begins to rise. These findings may contribute philanthropy research and non-profit sector literature, helping to determine better ways to give.
Keywords:	Social justice, agent-based modelling, econophysics, zakat, taxation
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	EXPLORING THE ADOPTION OF DIGITAL WALLETS AMONG ISLAMIC MILLENNIALS IN YOGYAKARTA, INDONESIA USING AN EXTENDED UTAUT MODEL: THE ROLE OF ISLAMIC CONSUMPTION ETHICS
Author:	ANTON PRIYO NUGROHO, DHIYAUL AULIA ZULNI, & YULI ANDRIANSYAH
Abstract:	The rapid advancement of technology is closely associated with the millennial generation, often referred to as the internet generation, nexters, or echo boomers. Compared to previous generations, the Islamic millennial generation exhibits a greater openness towards technology, particularly in embracing digital wallets for financial transactions. However, concerns arise regarding the potential impact of technological characteristics on the consumer ethics of Islamic millennials. To address this, the present study aims to explore the role of Islamic consumption in the utilization of digital wallets within the Unified Theory of Acceptance and Use of Technology (UTAUT) model. The study was conducted online, with a sample of 225 respondents from the Islamic millennial generation in Yogyakarta, selected through purposive sampling. The data analysis employed Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings indicate that performance expectancy, effort expectancy, and social influence positively influence the willingness of the Islamic millennial generation to adopt digital wallets. However, facilitating conditions and consumption ethics in Islam do not emerge as significant factors in determining the behavior of the Islamic millennial generation. This finding is noteworthy as it provides guidance for the adoption of digital wallets among millennials in Yogyakarta to prioritize product benefits, service quality, and social engagement rather than religious factors. From an Islamic consumption ethics perspective, this finding presents a challenge regarding the importance of educating Islamic values in consumption among millennials in Yogyakarta.
Keywords:	Islamic Consumption Ethics, Millennial Generation, Digital Wallet, UTAUT Model, Structural Equation Model
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	A MODEL OF ARTIFICIAL INTELLIGENCE IN CYBER SECURITY OF SCADA TO ENHANCE PUBLIC SAFETY IN UAE
Author:	OMAR ABDULRAHMANAL ALATTAS ALHASHMI, MOHD FAIZAL ABDULLAH, RAIHANA SYAHIRAH ABDULLAH
Abstract:	The UAE government has set its sights on creating a smart, electronic-based government system that utilizes AI. The country's collaboration with India aims to bring substantial returns through AI innovation, with a target of over $20 billion in the coming years. To achieve this goal, the UAE launched its AI strategy in 2017, focused on improving performance in key sectors and becoming a leader in AI investment. To ensure public safety as the role of AI in government grows, the country is working on developing integrated cyber security solutions for SCADA systems. A questionnaire-based study was conducted, using the AI IQ Threat Scale to measure the variables in the research model. The sample consisted of 200 individuals from the UAE government, private sector, and academia, and data was collected through online surveys and analyzed using descriptive statistics and structural equation modeling. The results indicate that the AI IQ Threat Scale was effective in measuring the four main attacks and defense applications of AI. Additionally, the study reveals that AI governance and cyber defense have a positive impact on the resilience of AI systems. This study makes a valuable contribution to the UAE government's efforts to remain at the forefront of AI and technology exploitation. The results emphasize the need for appropriate evaluation models to ensure a resilient economy and improved public safety in the face of automation. The findings can inform future AI governance and cyber defense strategies for the UAE and other countries.
Keywords:	SCADA systems; Public safety; Artificial intelligence; Cyber sabotage; Cyber defense; Cyber security;
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	IMPLEMENTING JERK FREE BLDC POSITION CONTROL USING SOC WITH FOURTH ORDER TRAJECTORY PLANNING
Author:	AJAY PAITHANE, SAKSHI PAITHANE, SUNIL DAMBHARE, MADHAV THIGALE, MUKIL ALAGIRISAMY
Abstract:	High Performance Motion Systems is essential for precise position of equipment used in the medical, automotive industries. Accomplishing the precise position with minimal time and vibration is a real challenge which makes design complex. Motion control system, typically requires three components- motor drive, electrical control hardware and control algorithm. Diligently determining each component of motion control is a crucial for high performance system and low development time. This paper demonstrates use of BLDC motor drive. The design and implementation of BLDC commutation and peripheral interfaces in programmable hardware logic in Zynq SoC processor as electrical control hardware. Fourth order trajectory Planning which improves the position accuracy and reduces vibration as a control algorithm can be used for high performance motion systems. The simulation result of FPGA control logic of BLDC commutation and peripheral interface demonstrate that processor can offload its task to FPGA. Test result for the hardware implementation affirms the accuracy and minimal vibration. Thus, Implementing BLDC motor as a Drive, Zynq SoC as control Hardware and fourth order algorithm as a control algorithm give high performance motion with ease of development time.
Keywords:	SoC, FPGA, Trajectory Planning, BLDC, Encoder, CAN
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	FACTORS AFFECTING SATISFACTION OF INTENTION TO REPURCHASE, INTENTION TO RECOMMEND, AND WILLINGNESS TO PAY MORE IN ONLINE FOOD DELIVERY APPLICATIONS
Author:	AUFRIDA MERNIAWANDA, SFENRIANTO
Abstract:	Customer satisfaction can be considered a primary factor in the usage of Online Food Delivery (OFD) applications. OFD applications have experienced rapid growth year after year, with Generation Z being one of the largest user groups utilizing OFD services. While there have been studies examining factors such as e-service quality, image, and trust in relation to customer satisfaction, there is limited research on the behavior of Generation Z regarding the usage of OFD applications. This study aims to determine the factors that influence customer satisfaction with intention to repurchase, recommend, and willingness to pay more on the OFD application. This study uses a quantitative method by collecting data through an online questionnaire of 300 Generation Z respondents who are customers of one of the OFD applications in Jakarta, Indonesia (xFood). Data analysis for this study uses the PLS SEM model by testing validity and reliability and testing hypotheses. The results of this research analysis show that e-service quality, image, and trust have a significant positive effect on customer satisfaction. In addition, customer satisfaction has a significant positive effect on customer behavior attitudes. E-service quality, image, and trust also have a significant positive effect on customer behavior attitudes through the mediation of customer satisfaction. The results showed that improving e-service quality, image, and trust carried out by the xFood application can increase customer satisfaction so that customers behace intention to repurchase, recommend, and willingness to pay more towards xFood.
Keywords:	Satisfaction, Online Food, Repurchase, Recommend, and Pay More
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	HACBLALIGN: A HIERARCHICAL ATTENTION-BASED DEEP LEARNING FRAMEWORK FOR PROTEIN REMOTE HOMOLOGY DETECTION AND FOLD IDENTIFICATION
Author:	K. GOPINATH, G. RAJENDRAN
Abstract:	Protein Remote Homology Detection and Fold Identification (PRHI) are the two most crucial steps in predicting protein structure. Even though many computational techniques like Multiple Sequence Alignments (MSAs) have been designed, those techniques were not able to create proper alignments due to the varying dimensions of a protein sequence. So, this paper presents a new progressive deep MSA technique to create a more suitable decision-making system for MSA of low similarity protein families. In this technique, a decision-making system is initially trained by the Hierarchical Attention-based Convolutional Neural Network (CNN) with Bidirectional Long Short-Term Memory (BLSTM) named HACBLalign to progressively align the given protein sequences by determining various posterior probability matrices. This model progressively builds a global alignment by aggregating essential subsequences alignment into sequence alignment. The attention level allows the model to choose qualitatively informative subsequences and sequences. As a result, high-quality MSA is obtained. Then, the top-N-gram and Auto-Cross-Covariance (ACC) features are extracted based on the Position-Specific Scoring Matrix (PSSM) from aligned protein sequences. Further, such features are fed into the CNN with a Softmax classifier to recognize protein homologies and folds. At last, the experimental results illustrate that the HACBLalign accomplishes a 92.4%, 92.5% and 92.1% accuracy on SCOP 1.53, SCOP 1.67 and superfamily databases respectively in recognizing protein homologies and folds compared to the conventional MSA techniques.
Keywords:	Protein Homology, Multiple Sequence Alignment, CNN, PSSM, Softmax
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	ECSI MODELLING FOR MSME CUSTOMER SATISFACTION DUE TO CASHLESS AND CASH TRANSACTIONS
Author:	MUHAMAD RIFKY ADHANI, MUHAMMAD ZARLIS
Abstract:	This paper aims to examine the effect of using traditional transaction (Cash) and non-cash transaction (Cashless) on customer satisfaction and loyalty in the MSME business using the European Customer Satisfaction Index (ECSI) model. ECSI is a model that can be used to figure out how strong and in which way do the things that affect customer satisfaction and loyalty. Collect 100 questionnaire data that will be used for the conceptual model. The collected data are analyzed according to the structural equation modeling technique using the SmartPLS software version 4. The statistics indicate that Cashless Transactions are more prevalent on daily transactions, but users of Cash Transactions tend to be the most significant on customer satisfaction and loyalty. Despite the widespread adoption of E-Wallets for Cashless Transactions, these tools have not proven effective in assisting MSME owners in fostering customer satisfaction and loyalty. The findings showed that trust variables had a positive influence on customer loyalty for cash transactions and cashless transactions, but there was no component that had an influence on customer satisfaction. This research is presumed to assist MSME actors in maintaining as well as enhancing customer satisfaction and loyalty, which is related to continuing to adopt Cash Transactions or improving MSME business using Cashless Transactions services.
Keywords:	ECSI, Loyalty, Satisfaction, Cashless
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	MACHINE LEARNING PIPELINE APPROACH TO SECURE IOT-BASED SMART CITIES
Author:	ABDESSAMAD BADOUCH, SALAHEDDINE KRIT
Abstract:	The data stored and transmitted in IoT-based smart cities is often huge and highly sensitive. One of the major threats to data in IoT-based smart cities is network intrusions and attacks. Various algorithms have been proposed to mitigate these attacks with high accuracy. However, most of them have major flaws, such as high detection times and the limitation of only being able to perform binary classification of network traffic. In this paper, we propose a new Machine Learning (ML)-based approach for intrusion detection in IoT-based smart cities. The proposed approach performs the detection in a pipeline of three phases: (1) preprocessing of incoming network traffic; (2) binary classification of traffic data into normal or attack; and (3) perform a final multi class classification phase. The experiments were performed on the TON-IoT public dataset, and after a comparison study of several ML algorithms, we settled to use Decision Tree (DT) for the binary classification phase and Random Forest (RF) for multi class classification. In addition to high accuracy, our approach achieves better computation time, and more fine-grained detection of attacks, which are highly important for intrusion detection systems. This aspect should not be overlooked in the context of IOT devices, which usually have very limited computational resources.
Keywords:	IOT, Smart Cities, Machine Learning, Security, Privacy
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	GENERALIZED METHOD OF SITUATIONAL DECOMPOSITION AND MULTIFUNCTIONAL INTELLIGENT CONTROL SYSTEMS
Author:	U. UMBETOV, KHU WEN-TSEN , P.S. BELYAEV, YU. SHARIPOVA, SEITMURATOV A. SHЕKEYEVA K.
Abstract:	A fundamentally new type of automated optimal control systems, characterized as multifunctional intelligent systems, is considered. Their distinguishing feature is the ability to implement various control tasks depending on the circumstances that determine the required behavior of the control object. Such systems have a high degree of autonomy, including the ability to operate in a fully automatic mode, which increases their reliability and survivability. The proposed generalized method of situational decomposition forms the mathematical basis of the considered control principle. Its essence lies in the fact that in order to develop control decisions in the control system, a finite set of different tasks adapted to certain situations is used. In the process of functioning, the control system independently evaluates the situations that arise and sets the necessary control task for execution. The proposed developments seem to be extremely important and interesting from the point of view of building self-tuning control systems with increased autonomy. Such systems are relevant for complex technological processes, technological processes with variable configuration, discrete technological processes, aircraft and sea vessels, spacecraft, unmanned vehicles, multifunctional robots, including combat drones.
Keywords:	Multifunctional Control, Optimal Control, Intelligent Control, Hierarchical Control System, Reliability Of Control Systems, Survivability Of Control Systems, Autonomy Of Control Systems, Control Systems For Industrial Objects Of A Discrete Type, Control Systems For Objects With A Variable Structure, Control Systems For Multifunctional Robots And Drones.
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	A NOVEL SWITCHING TECHNIQUE BY dSPACE CONTROLLER FOR DC-DC LLC CONVERTER FOR ELECTRICAL VEHICLE CHARGING
Author:	P VAMSI KRISHNA, SHAIK SHABANA, KASIBHATLA RAMA SUDHA, A.CHANDRA SEKHAR
Abstract:	As the LLC resonant converter excels in efficiency, power density, and input/output voltage control, it is widely used in battery charging applications. High efficiency and power density are becoming more necessary as the market for ultra-fast battery chargers for electric vehicles expands rapidly. LLC resonant converters are popular because of their great efficiency and minimal switching loss. In this research, the small-signal model of a limited-loop-feedback (LLC) resonant converter is developed using the notion of extended description functions. The large-signal limited liability company model is derived using the first-order harmonic approximation technique. These converters are often used in battery chargers, electric cars, and high-efficiency power supply because of the stringent output voltage requirements required by these devices. This paper presents dual-loop control technique, where an inner current loop and an outside voltage loop are established. An LLC dual first order small-signal model with reduced parameters is provided for use in controller design and tuning. For the sake of this study, we will focus on one-loop control (voltage control loop control with LLC). The DC-DC LLC converter with a switching-frequency feed forward. In this paper the main focus was on switching of LLC resonant converter with the help of dSPACE controller which was different from other LLC resonant controllers so that by varying the switching frequency the inductor and capacitor values can be varying in nature for same output voltage so we can practically able to get inductor and capacitor components available for prototype construction. Using mat-lab and Simulink, we propose the gain/phase and pole position at different operational points.
Keywords:	Resonant Converters, Resonant Frequency, Electric Vehicles, State Space Model
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	INVESTIGATION OF OPTIMAL TASK OFFLOADING AND RESOURCE ALLOCATION USING HYBRID GREY WOLF LION OPTIMIZATION (HGWLO) IN CLOUD–EDGE COMPUTING
Author:	K.VINOTHKUMAR, DR. D. MARUTHANAYAGAM
Abstract:	The two main components of edge computing are task offloading and resource allocation. System energy consumption can be reduced and task processing times increased with a sensible job offloading and resource allocation plan. The vast majority of existing research on the task migration of edge computing only takes the resource distribution between terminals and edge servers into account, completely excluding the enormous computing resources in the cloud centre. Under cloud edge computing, Hybrid Grey Wolf Lion Optimization (HGWLO) using job offloading and resource matching method was presented in order to adequately utilise cloud and edge server resources. This research study establishes the job offloading decision of many end-users as a task scheduling in cloud edge computing with the experimental findings showing the that the suggested algorithm outperforms other pre-existing algorithms of dragonfly, grey wolf, and lion optimization with regard to Makespan, Energy Latency and Energy Consumption, System Utility, Task Completion Time, Execution Delay, and Convergence Rate.
Keywords:	Edge Cloud Computing, Resource Allocation, Task Scheduling, Lion Optimization Algorithm, Grey Wolf Optimization.
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	A NEW APPROACH OF LEAF DISEASE DETECTION USING BAG OF VISUAL WORDS
Author:	MOULAY HAFID AABIDI, ADIL EL MAKRANI, BRAHIM JABIR, IMANE ZAIMI
Abstract:	The implementation of an image classifier based on the "Bag of Visual Words" model is discussed in this paper, which is a variation of the Bag-of-Words model utilized in information retrieval. The Bag-of-Words model has been extensively applied to object recognition, image retrieval, and scene classification by treating visual features as "visual words". By constructing a histogram of visual words from the "dictionary", which in this study is the training images, each image can be uniquely represented as a document. While many deep learning models have now become industry standards for image classification, there were classical techniques for image classification that existed before the advent of deep learning. Therefore, we propose to explore the Bag of Visual Words approach as one of these techniques. The main goal of this study is to provide deep learning researchers with a guideline for their research projects in various fields, including medicine, agriculture, aeronautics, and other areas. The studied model achieved an overall accuracy of 70.08%, which is within the benchmark accuracy range of classical techniques.
Keywords:	Bag of Visual Words (BoVW), Artificial Intelligence, Machine Learning, Deep learning, Image classification, Leaf Disease Detection
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	NAVIGATING THE TRUST, TECHNOLOGY FIT, AND PERFORMANCE EXPECTATION IN THE ADOPTION OF BIG DATA ANALYTICS IN GOVERNMENT AUDITING
Author:	KEVIN RIVALLDO, RINDANG WIDURI
Abstract:	The Audit Board of the Republic of Indonesia (BPK) is a state institution in Indonesia that conducts financial and non-financial audits of other Indonesian state institutions. Big Data Analytics is essential to apply in BPK, where in auditing Indonesian government institutions, BPK has various forms of unstructured, heterogeneous data. Various types of heterogeneous data in BPK are financial and non-financial data that are integrated. Unstructured data can be in the form of text mining (data acquisition through social media). The application of Big Data Analytics in BPK is based on several factors. This study aims to determine the factors influencing BPK in adopting Big Data Analytics using the Initial Trust approach model, Task Technology Fit, and Performance Expectations. Accounting Firms can reference this research in adopting Big Data Analytics during their audit process. This study was conducted by distributing questionnaires, where the study population was 103 people, and the data obtained were 77 respondents. The analysis method in this study uses SEM (Structure Equation Modelling) and PLS (Partial Least Square) approach with Smart PLS software. This study reveals that Personal Propensity to Trust and Structural Assurance positively affect Initial Trust. Initial trust and performance expectations influence Behavioral Intention. Both technological and Task characteristics influence Task Technology Fit. In the meantime, Task Technology Fit has a negative impact on the Behavioral Intention of Big Data Analytics by the Indonesian AuditBoard's auditors. This research contributes to Accounting Firm and BPK in adopting Big Data Analytics through the perspective of the Initial Trust model, Task Technology Fit, and Performance Expectations.
Keywords:	Big Data Analytics, Initial Trust, Task Technology Fit, Performance Expectation, Behavioral Intention
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	INVESTIGATION OF HOW VARIABLES IMPACT INDUSTRY MODEL IN SMART CITY: EXPLANATION WITH SHAP VALUES
Author:	IMANE DAHA BELGHITI, MOUNA ELMACHKOUR
Abstract:	In the present era, the implementation of smart cities involves the utilization of various smart sensors to gather data. These sensors transmit their collected data to servers for analysis. However, this process requires additional available channels for data transmission. With the increased usage of Internet of Things (IoT) devices, the frequency band becomes overcrowded. To address this issue, one possible solution is to employ opportunistic access methods like cognitive radio. This article focuses on the utilization of Machine Learning (ML) to forecast the performance of IoT cognitive radio (IoTCR) sensors. The decisions made by the ML model are explained using Explainable Artificial Intelligence (XAI) techniques such as the Shapley value (SHAP). The significance of SHAP lies in its ability to clarify the outcomes of ML models, which is crucial for ensuring their quality. To demonstrate the effectiveness of XAI, the article presents a case study in the industrial sector where ML quality is improved through its implementation.
Keywords:	Smart sensor, XAI, Machine learning, IOT, Cognitive Radio, Smart City
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	A PARALLEL SPARSE DATA COMPRESSION (PSDC) METHOD FOR FILE STORAGE OPTIMIZATION USING CLOUD ENVIRONMENT
Author:	N.SRIKANTH, T.PREM JACOB
Abstract:	Huge, distributed data-intensive applications consume data at fast speeds, causing adverse I/O effect on storage services while managing data. Cloud computing is the future of data storage, communication, and resource sharing. Cloud computing makes data-intensive applications appealing to a wider public who cannot afford pricey large-scale distributed infrastructures. Compressing large amounts of intense application data for internet transmission saves time and storage capacity. This study proposes Sparse Data Compression Algorithm (SDC) to reduce memory entries and reduce storage space. Conventional compression technology cannot process big data with a high compression rate and low energy cost. Using the Cloud framework, this study implements Parallel Sparse Data Compression (PSDC), a high-speed lossless data compression algorithm. The PSDC algorithm chunks data compression data and submits to cloud virtual cores to reduce computational complexity. PSDC in the cloud environment speeds up compression and improves ratio. Eventually, the proposed method outperforms standard compression algorithms in compression ratio, compression size, and compression time.
Keywords:	Data-intensive applications, Cloud Computing, Data Compression, Parallel Computing, and Sparse Representation.
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	MATH WORD PROBLEM SOLVERS: A REVIEW OF DATA DRIVEN APPROACHES AND DATASETS
Author:	HARSHAL KOTWAL, GIRISH KUMAR PATNAIK
Abstract:	Math Word Problem (MWP) solving is the process of finding the value of an unknown quantity in a word problem expressed in any Natural Language. The development of computer algorithms that can automatically solve arithmetic word problems is a challenge for the Artificial Intelligence research community. Solving Math Word Problems has recently become a significant research domain because automatically generating solution equations requires understanding natural language and its representation in computer understandable manner. This task is classified as natural language question-answering which is a well-studied problem in Natural Language Processing that requires machine common sense as well as domain knowledge and reasoning abilities. Solving a math word problem is particularly challenging due to the semantic gap in translating natural language text into machine-understandable logic that enables reasoning. To transform problems into several predefined templates in classification or retrieval style, early techniques depend on either predefined rules or statistical machine learning-based algorithms. Following the success of Machine Learning-based algorithms in a variety of domains, researchers have recently experimented with automatically solving Math Word Problems using large datasets. This research paper examines the performance and results of Data-Driven approaches to Solve Math Word Problems. The research also includes state-of-the-art small and large datasets used for performance evaluation of various approaches. The goal of this study is to help scholars understand the obstacles to solving Math Word Problems and to guide and motivate them to contribute in this direction.
Keywords:	Artificial Intelligence, Math Word Problems, Machine Learning, Natural Language Processing, Neural networks
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	DEVELOPMENT OF DIGITAL MEDIA BASED ON VISUAL NOVEL (PROS-VN) TO IMPROVE PROSOCIAL BEHAVIOR IN EARLY CHILDHOOD
Author:	DADAN NUGRAHA, FASLI JALAL, SOFIA HARTANTI
Abstract:	One of the most important aspects of development for early childhood is the aspect of prosocial behavior. Several media are needed to improve this aspect of development, including digital-based media. emotional. Based on that, this research aims to develop media based on digital visual novels to improve prosocial behavior in early childhood. The ADDIE model with 5 main stages namely Analyze, Design, Develop, Implement, and Evaluate and the subject is children aged 5-6 years. Through observe Research data can be obtained and analyzed through observation, interviews, and documentation with the N-gain score analysis technique application as a digital innovation product in this study in the form of early childhood education media designed to be used on computers with the Android operating system. PROS-VN is a digital-based game application to improve early childhood prosocial behavior that focuses on narrative. PROS-VN digital media is effective in increasing prosocial behavior in early childhood. Researchers and developers of early childhood education media should focus more on aspects of developing children's potential so that every aspect that is stimulated through digital media can be utilized in their lives in the future.
Keywords:	Mathematical Digital Media, Visual Novel, Prosocial Behavior
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	AUTOMATED TOMATO LEAF DISEASE DETECTION TECHNIQUE USING DEEP LEARNING
Author:	DIPRA MITRA, ANKUR GOYAL, SHIKHA GUPTA3, HOSHIYAR SINGH KANYAL, SHIVKANT KAUSHIK, KAILASH KUMAR
Abstract:	Artificial intelligence is the most common and comprehensive common-sense cognitive engine in the ecosphere. Essentially affluent are both the cloud SaaS business model and the concept of an AI business platform. Early infection detection is one of the most efficient ways to keep plants healthy in a complicated environment since it links to artificial intelligence (AI) systems that can communicate with other digital systems. Plant disease detection has been digitized and data-driven with the growth of smart farming, which could make decisions automatically and intelligently, as well as smart analytics and management. This is as a result of continuous developments in computer vision. Due to AI-based ML and DL, the area of digital image processing has recently made tremendous strides. Researchers are interested in learning more about how to employ a good machine learning or deep learning model to identify plant ailments because when pests attack plants and crops, it has an impact on the nation's agricultural productivity. Farmers or specialists will often utilize their unassisted eyes to detect and identify plant disease. But this method could be costly, time-consuming, and incorrect. Automatic detection using image processing techniques yields rapid and reliable results. This study investigates a unique approach to classifying Tomato leaf images using deep neural networks and building a diagnostic model for plant illness. As computer vision research and development broadens and improves accurate plant protection, the market for computer vision applications in precision agriculture may grow. the creative teaching techniques, methodology, and approach enable for a quick and simple system installation in this article. The automated plant disease detection method's data collecting, segmentation, feature extraction, and classification phases are also detailed.
Keywords:	Plant Disease Detection, Artificial Intelligence, Machine Learning, Agriculture Automation
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	GEOSTATISTICS AND DIGITAL IMAGE ANALYSIS FOR OPTIMIZING RICE PRODUCTION
Author:	FRANS RICHARD KODONG, MOHD. FAIZAL BIN ABDOLLAH, MOHD. FAIRUZ ISKANDAR BIN OTHMAN
Abstract:	Rice, as the staple food for a significant majority of the Indonesian population, plays a crucial role in food security and socio-economic stability. To address the strategic challenges associated with rice production, this study focuses on utilizing geostatistics and digital image analysis techniques to optimize rice production and enhance agricultural practices. The key factors influencing rice production, including land area, fertilization, seed varieties, human resources, and agricultural technology, are examined in relation to food security concerns. Fertilizers, high-yielding varieties, and water availability emerge as vital elements for increasing national rice production. However, the efficiency and effectiveness of fertilization practices are heavily influenced by localized conditions, and current approaches often lack rationality and balance. To achieve efficient production and rationalize fertilization practices, this research proposes the application of geostatistics and digital image analysis techniques. Geostatistical models, specifically the Kriging Method, are employed to predict the spatial distribution of key nutrients and fertilizers, such as Sodium, Phosphorus, and Potassium (NPK), required by rice plants in paddy fields. Additionally, digital image processing and computer vision technologies are utilized to automate the assessment of nutrient adequacy based on leaf color analysis. This advancement replaces the previous manual comparison method, providing a more accurate and efficient approach. The integration of geostatistics and digital image analysis offers a promising solution to optimize nutrient management, precision fertilization, and overall rice production. By harnessing advanced technologies and data-driven approaches, this study aims to contribute to the development of sustainable agricultural practices, ensuring improved food security and socio-economic well-being for the Indonesian population.
Keywords:	Geostatistics, Digital Image Analysis, Rice Production, Nutrient Management, Precision Fertilization, Food Security.
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	ANALYZING CHINA S DEFENSE POLICY IN THE NEW ERA FROM A THREAT PERSPECTIVE USING ANALYTICAL NETWORK PROCESS
Author:	DWI SOEDIANTONO, AMARULLA OCTAVIAN
Abstract:	The international world has undergone major changes along with the development of globalization. These changes include economic aspects, information that is increasingly accessible to the public, and growing cultural diversification. In addition, it also affects the national defense system. It causes a country to be able to make a policy to protect the national defense, such as the United States and China. The theoretical review used in this paper is the concept of national defense. The method used is qualitative by collecting information through a literature study. The result of this paper is that China has issued a defense white paper containing China's defense policies in a new era where China is carrying out a defensive defense strategy. China's defense policy is made to deter threats from outside and from within the country. China, which has become a major power in the world, has forced China to be able to compete with the United States in terms of state defense and security, so it is necessary to have a defense development policy that can be pursued through international cooperation as one way that can be taken.
Keywords:	Defensive; Globalization; National Defense; International Cooperation, Analytical Network Process (ANP).
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	A FUZZY LOGIC MODEL FOR ENSURING CUSTOMER SATISFACTION AND PREVENTING COMPLAINTS ABOUT QUALITY DEFECTS
Author:	ANASS MORTADA, AZIZ SOULHI
Abstract:	Customer satisfaction has become a key element in a competitive business world. This pushes companies to improve the quality of their products in order to meet customers' expectations and ensure their trust and loyalty, as well as to focus their efforts on problems and defects that may lead to complaints or even the loss of customers. This is one of the most critical and decisive issues for companies and a key element in remaining competitive. The objective of this paper is to develop a fuzzy logic model that facilitates the decision on the defects that are prioritized for actions and solutions by estimating the value of the complaint risk for each defect based on the indicator of occurrence and the indicator of defect detection. Our model has shown the importance of acting mainly on the detection of defects through robust systems of control of the parts in addition to taking action on the reduction of the occurrence of defects, with the proposal of effective Lean tools: 5 Whys, Ishikawa Diagram, Poka Yoke, and Jidoka, to improve the two input indicators. This allows a considerable mastery of the quality of the delivered products, thus maintaining customer satisfaction while remaining safe from the risk of complaints. The combination of fuzzy logic, which is an artificial intelligence tool, with lean manufacturing tools to prevent the risk of customer complaints is one of the basic advantages of merging Industry 4.0 and lean management within the framework of Lean 4.0 to better achieve operational excellence in companies.
Keywords:	Quality, Customer complaints, Fuzzy logic, Artificial Intelligence, Decision-making, Lean 4.0.
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	AN IOT-BASED COMPUTATIONAL INTELLIGENCE MODEL TO PERFORM GENE ANALYTICS IN PATERNITY TESTING AND COMPARISON FOR HEALTH 4.0
Author:	VIJAY ARPUTHARAJ J, K. SANKAR, A. SENTHIL KUMAR, MULAGUNDLA SRIDEVI, D.DURGA PRASAD
Abstract:	Parental comparison and parenthood testing are essential in various legal and medical scenarios. The accuracy and reliability of these tests heavily rely on the gene analysis algorithms used. However, analyzing the quality of succession data are quite challenging due to the presence of detrimental characteristics. To address this issue, we propose using machine learning-based algorithms such as clustering (Correlation-based) and Classification (Modified Naive Bayesian) to separate these characteristics from the parent-child gene array. This progression helps to identify, validate, and select tools, techniques for scrutinizing indecent sequences, leading to accurate and reliable results. In this paper, we present an IoT-based intelligence tool for parental comparison that uses a secure gene analysis algorithm. The model employs multiple sensors and devices to collect genetic data, which is then securely processed and analyzed using contemporary algorithms. The suggested model uses advanced techniques such as encryption and decryption to ensure the privacy and confidentiality of the genetic information. Our experimental consequences reveal that the proposed model is reliable, secure, and provides accurate results. The model has the potential to be used in various legal and medical contexts where the security and reliability of genetic data are critical.
Keywords:	Iot, Correlation Clustering, Gene Analysis, Paternity Testing.
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	AGENT-BASED MANAGEMENT AND COORDINATION OF AIRCRAFT AT INTERSECTIONS
Author:	ELHOUCINE OUASSAM, YASSINE DABACHINE, NABIL HMINA, BELAID BOUIKHALENE
Abstract:	This work presents a game-theoretic approach to address the problem of coordination and scheduling of aircraft at intersections, with the goal of avoiding conflicts and potential collisions. The proposed algorithm enables simple agents to work together in a way that leads to cooperative behaviors, resulting in equilibria that improve the overall efficiency of the system. We tested and compared the game-theoretic approach with a centralized approach, namely the First-Come-First-Serve (FCFS) principle, using data from Mohammed 5 Casablanca airport. The initial results suggest that the game-theoretic model is promising, despite its higher complexity. The approach has the potential to improve the overall coordination and scheduling of aircraft, leading to a more efficient and safe system. The proposed game-theoretic approach is designed to improve the coordination and scheduling of aircraft at intersections, ultimately leading to a safer and more efficient system. The approach is shown to be promising in initial testing, offering a potentially superior alternative to centralized approaches like FCFS. This research highlights the potential benefits of game-theoretic models in addressing complex coordination problems in multi-agent systems.
Keywords:	Agent-Based Modeling, Cooperative Agent, Distributed Computing, Game Formalism, Scheduling Of Aircraft
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	AN ANALYSIS OF STUDENT PERCEPTIONS OF BLOCKCHAIN TECHNOLOGY AND ITS IMPLICATIONS FOR EDUCATION
Author:	FELIX PUTRA ASTAMAN, TUGA MAURITSIUS
Abstract:	This study evaluates student perceptions of blockchain technology and its implementation in education. This research was conducted using the interview method with Bina Nusantara University students majoring in Information Systems and analyzed using the NVivo software. The results of this study indicate that students have a positive perception of blockchain technology and see the potential it embodies in the process of verifying educational qualifications, learning management, payment and management of educational debt, educational inclusion, distance learning, and management and distribution of educational assistance. However, students are also aware of security and privacy issues that may arise in the use of blockchain technology in education. Word Cloud also pointed out that the words that frequently came up from the interview results were "security", "accountability", "transparency", "validity" and "authentication". In addition, the results of this study also show that students see the potential of blockchain technology in the management of educational data and information, with the ability to store secure and verified data automatically. Students also see the potential of blockchain technology in increasing efficiency and effectiveness in educational administration processes. However, students also realize that implementing blockchain technology in education requires clear regulations and standards as well as support from the government and industry. The conclusion of this study is that Bina Nusantara University students have a positive perception of blockchain technology and see its implicit potential in education. The advice given by students is that there is a need for higher education and awareness about blockchain technology as well as the development of infrastructure and regulations needed for the implementation of blockchain technology in education.
Keywords:	Blockchain, Education, Students, Qualitative, Perception
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	ANALYSIS OF THE CRITICAL SUCCESS FACTORS OF E-GOVERNMENT ADOPTION: A SYSTEMATIC REVIEW OF LITERATURE
Author:	TANTY OKTAVIA, BAYU REZKY HEMUNANTIO, HENRIKUS ERIC SETIAWAN, IDHAM KHALID MAHASIN
Abstract:	Nowadays, Information and Communication Technology (ICT) changes how people engage with each other because these technologies encompass all the services that involve computing, data management, communications provision, and the internet. It also deals with the transmission and reception of information. ICT improves people's lives by providing newer, better, and faster methods for them to communicate, network, seek support, access information, and learn. ICT is used as a support tool for good governance development, so it allows for higher levels of effectiveness and efficiency in governmental tasks. This research aims to find out what are the critical success factors of E-Government adoption by using the Systematic literature review methods and approaches. CSF's primary objective is to promote the development of electronic government to be more efficient by eliminating the less impactful factor and focusing more on the important one. This research targeting the papers published in 2014 – 2022 based on president’s law number 96 year of 2014, Pitelabar the Governmental plans about E-government development. The results are that we found 74 kinds of Critical success factor through all the papers that has been reviewed, and perceived ease of use is the most common CSF by being found in 12 papers.
Keywords:	Implementation, E-Government, Adoption, Stakeholders, Critical Success Factor
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text

Title:	PERFORMANCE ANALYSIS OF RATE ADAPTATION ALGORITHMS BASED ON PARAMETERS MOBILITY MODELS AND PROPAGATION LOSS IN WIRELESS LANs
Author:	M SRI VAISHNAVI, T NISHITHA, Dr. T ADI LAKSHMI
Abstract:	Computer networks establish our day-to-day communications in this contemporary world. Wireless LANs (WLANs) have been beneficial for network connections within a small area referred to as a local area network. WLANs are elicited from the IEEE 802.11ac standard which is used in this paper. As WLANs are widely used for networking purposes the challenge is to maintain and improve the performance of Wireless LANs . . . . Therefore, rate adaptation algorithms are applied to the system to enhance the working conditions of Wireless LANs. This paper primarily focuses on the performance of a few rate adaptation algorithms by changing different parameters like mobility models and propagation loss to note down the changes and efficiencies in various conditions based on metrics like average throughput and average delay so that their usage can be improvised in our daily lives.
Keywords:	IEEE 802.11ac, Wireless LANs, Rate Adaptation Algorithms, Mobility Models, Propagation Loss Model, Performance Analysis, Throughput, Delay
Source:	Journal of Theoretical and Applied Information Technology 31^st July 2023 -- Vol. 101. No. 14-- 2023
Full Text