Information Technology Demands Research Articles

Spatial mapping and alignment of SHS, HEIs, and Industry in Northwestern Leyte

This study examines the spatial distribution and alignment of Senior High Schools (SHS), Higher Education Institutions (HEIs), and industries in Region VIII, focusing on the interconnections between geographic, educational, and economic factors. Key areas of analysis include Ormoc City, Albuera, Kananga, Isabel, and Palompon. Urban centers like Ormoc City host a high concentration of SHS offering diverse tracks such as Science, Technology, Engineering, and Mathematics (STEM) and Accountancy, Business, and Management (ABM), catering to the demands of Information Technology (IT) and business industries. In contrast, rural areas focus on technical-vocational (TVL) tracks aligned with agriculture and fisheries but often lack alternative career pathways. HEIs are concentrated in Ormoc City, creating accessibility challenges for rural students and limiting program diversity in industrial hubs such as Isabel and Palompon. Although there is strong alignment between TVL tracks and agro-industrial needs in Albuera and manufacturing demands in Isabel, significant gaps remain, including inadequate IT specialization to meet Ormoc City’s industry needs, limited HEI capacity for STEM graduates in rural areas, and insufficient business management programs in Palompon. These findings provide actionable insights for policymakers, educators, and industry stakeholders to address educational gaps and strengthen regional economic development.

Predictive Regression Modeling for Forecasting Graduation Duration in Online Offsite Degree Program

The demand for Information Technology (IT) professionals continues to rise across various sectors, where theyplay vital roles. However, the supply of IT graduates often fails to meet industry needs and this is a huge problem for the SriLankan IT Industry (National IT-BPM Workforce Survey – 2019). In this context, this study presents a predictive regressionmodelling approach to predict graduation duration in the Bachelor of Information Technology (BIT) degree program at theUniversity of Moratuwa, Sri Lanka. It integrates demographic data—student district, birth year, AL results, OL maths grade,gender, employability status, occupation, and AL stream—along with academic performance indicators like diplomacompletions and higher diploma completions. After evaluating the suggested features, the key findings indicate thesignificance of certain features, notably the number of semesters taken to complete the diploma, higher diploma, and thedegree. Additionally, demographic factors such as district, birth year, AL results, OL maths grade, gender, and employabilitystatus were found to be important. The regression analysis was carried out using the Orange data mining tool (Orange DataMining). Various algorithms, including random forest, neural network, linear regression, and k-nearest neighbours (kNN),were used to develop predictive models. By adjusting parameters such as metrics, weights, number of neighbours, numberof iterations, and training dataset size, the models were optimised to better fit the dataset. Training and testing the modelsrevealed consistent error metrics, including MSE, RMSE, MAE, and R^2, validating the accuracy of predictions. Byconsidering the least and reasonable error in each model, the most suitable model to fit the given dataset was selected.The prediction model accurately forecasted graduation duration for subsequent academic batches, demonstrating itseffectiveness in predicting student progress in the program. This research contributes to understanding the factorsinfluencing graduation duration in a distance learning context and provides insights for educational institutions to optimiseprogram planning and student support initiatives. Additionally, it is a good indicator to the companies to gain a betterunderstanding of the availability of future workforce.

A Brief Discussion on the Application of Financial Software in Higher Education Institutions

With the arrival of a new management era and the digital age in higher education, the survival environment, operation, and management models of universities have undergone significant changes. Traditional financial software no longer meets the management needs of modern institutions. By selecting appropriate financial software, universities can accelerate the integration of internal information and the utilization of resources. Among these, cost control is a key financial aspect that universities are currently most concerned about. As the scale of operations expands and the total funding increases, the volume of reimbursement transactions has seen exponential growth. The diversification of financing methods has broadened the scope of economic activities in higher education, directly impacting the financial departments by expanding the scope and content of financial work and increasing the daily accounting tasks. Consequently, the workload has significantly increased. The complexity of financial work in universities has risen, leading to prominent issues such as low business approval efficiency, long wait times for employees, and high pressure on financial audits. The development of financial software has also driven an increasing demand for information technology in financial departments. The traditional reimbursement methods can no longer adapt to the current development status and management needs of universities, making the informatization of financial management an inevitable trend.

Securing Network Log Data Using Advance Encryption Standard Algorithm And Twofish With Common Event Format

The rapid advancement of information technology demands enhanced security for data exchange in the digital world. Network security threats can arise from various sources, necessitating techniques to protect information transmitted between interconnected networks. Securing network logs is a critical step in strengthening overall network security. Network logs are records of activities within a computer network, including unauthorized access attempts, user activities, and other key events. This research focuses on developing a network log security system by comparing the performance of the Advanced Encryption Standard (AES) and Twofish algorithms, integrated with the Common Event Format (CEF) for encrypting network logs. Tests were conducted on network log datasets to evaluate system functionality and performance. Results indicate that the AES algorithm performs encryption and decryption faster than Twofish. Across five tests with different file sizes, AES took an average of 2.1386 seconds for encryption, while Twofish required 22.8372 seconds. For decryption, AES averaged 2.451 seconds compared to Twofish’s 26.140 seconds. The file sizes after encryption were similar for both algorithms. Regarding CPU usage, AES demonstrated higher efficiency. The average CPU usage during AES encryption was 0.5558%, whereas Twofish used 23.2904%. For decryption, AES consumed 0.4682% of CPU resources, while Twofish required 13.7598%. These findings confirm that AES is not only faster in both encryption and decryption but also more efficient in terms of CPU usage. This research provides valuable insights for optimizing network log security by integrating standardized log formats, like CEF, with appropriate encryption techniques, helping to safeguard against cyber threats.

Disasters and technological upgrading measured by changes in demand for ICT labour: estimating the impacts with text

AbstractExtensive literature has studied the economic impact of disasters. However, specific impacts on labour markets have received less attention. Using a massive earthquake (> 8.0 Mw) that struck Chile in 2010 and proprietary data from a Chilean online job board (4136 job postings published between 2008 and 2012), we examine changes in demand for Information and Communications Technologies, ICT, related labour as a proxy for technological upgrading, by assuming that ICT and related technologies drive much of the technical change in production. We implement a structural topic model to discover and estimate the difference in the prevalence of ICT and Construction labour, among others. Our results show that ICT labour does not change. In contrast, Construction labour significantly differed after the disaster, suggesting that reconstruction activities led to employment differences. Our results suggest that there was no substantive technological replacement following the earthquake.

Improving Employee Performance Effectiveness Strategy In Implementing Hybrid Working At Switching Service Companies

One of the impacts of the COVID-19 pandemic on industries in Indonesia is the implementation of strict mobility restrictions, including in the IT industry. The increased demand for online services and information technology has driven development and innovation to create new ideas in the application of information technology across various fields, such as e-commerce, online learning, work from home (WFH), and others. This study aims to analyze the factors influencing employee performance and formulate strategies to improve employee performance effectiveness in the implementation of a hybrid work system in switching service companies. The study involves 83 samples using probability sampling techniques with simple random sampling. Data processing employs the Confirmatory Factor Analysis (CFA) method and the Structural Equation Modeling (SEM) method. The results show that Work Environment, Technology Infrastructure, Work Efficiency, and Intrinsic Motivation have a significant direct impact on Employee Performance, and Work Autonomy has a significant indirect impact through the Intrinsic Motivation variable on Employee Performance. However, Work Autonomy does not have a significant direct impact on Employee Performance. Several recommendations include efforts to address issues hindering performance achievement, particularly in cases where employees experience a decline in performance when the hybrid work system is implemented. To enhance employee performance, companies can take strategic steps in several crucial aspects, such as work environment, technology infrastructure, work efficiency, and intrinsic motivation.

Hubungan Berpikir Kritis Terhadap Hasil Belajar Siswa Kelas XI SMAN 3 Palopo

The development of information and communication technology demands that learners enhance their critical thinking skills to be able to filter accurate information, thereby achieving truth and a proper understanding of the knowledge around them. This is also expected to help improve students' learning outcomes. The research used in this study is quantitative descriptive research with the aim of determining the relationship between critical thinking skills and student learning outcomes in biology, specifically in the digestive system topic for Grade XI. The research subjects used were all Grade XI science students at SMA Negeri 3 Palopo. The determination of the subjects used the Slovin formula, resulting in a sample size of 147 students. The sampling technique employed was purposive sampling. Data collection in the research utilized two instruments: a critical thinking skills test consisting of 10 essay questions adjusted to the critical thinking skill indicators according to Ennis and a learning outcomes test consisting of 20 multiple-choice questions adjusted to the cognitive dimension indicators of Bloom's revised taxonomy according to Anderson & Krathwohl. Data on critical thinking skills and student learning outcomes were analyzed descriptively, and prerequisite tests were conducted using the Kolmogorov-Smirnov normality test and simple linearity tests. The relationship between critical thinking skills and student learning outcomes was tested using the product-moment correlation test, and the results obtained indicate a very strong and positive relationship between critical thinking skills and learning outcomes. This research is expected to provide insight to educators in their efforts to enhance students' critical thinking skills. Keywords: Learning outcomes, Critical thingking, Digestive sytem

A Study on the Practical Demand of Information and Communication Technology in Mine Rehabilitation Projects and the Basic Feasibility of Augmented Reality Technology

A Study on the Practical Demand of Information and Communication Technology in Mine Rehabilitation Projects and the Basic Feasibility of Augmented Reality Technology

A Digital Instructional Book: A Tool For Improving Students' Learning Outcomes on the Redox Reaction

The rapid development of information and communication technology demands the production of digital products. This study aims to produce a digital instructional book based on Balinese local cultures to enhance the learning outcomes of high school students. The development of this book used the ADDIE model. The analysis phase included an analysis of the chemistry curriculum, teachers’ and students’ opinions about digital books, digital learning, and Balinese local cultures related to the chemistry content. The design phase included creating a framework and preparing a digital instructional book based on Balinese local cultures. The development phase included validation by content, language, and media experts. The implementation phase included testing the practicality and effectiveness of the book. The evaluation phase was carried out at all phases of the ADDIE model. The characteristics of this book were that it was made in a digital form and integrated with local Balinese cultures. It met the criteria of being a very valid category based on content, language, and media aspects. It also met a practical and effective category to improve students’ learning outcomes. It is very useful to enhance chemistry learning outcomes in the era of the Industrial Revolution 4.0.

Effective Intrusion Detection System Using Deep Learning for DDoS Attacks

An increasing demand for information technology and cloud computing has led to various security threats over internet. Amongst all types of threats, Distributed Denial of Service (DDoS) attacks are the most common, posing a challenge to a cyber security. It allows unauthorized users to gain access to services, and preventing authorized users. Traditional intrusion detection, antivirus software, and firewalls are not enough to detect these attacks. This paper proposed an efficient deep learning-based intrusion detection system (IDS) for DDoS attacks detection. Proposed model is a hybrid CNN-LSTM model which is combination of best DL algorithms to take advantage of CNN to extract spatial features and LSTM to extract temporal features. The real-time DDoS-specific benchmark-dataset CICDDoS2019 used for training, testing, and validation. An autoencoder has been used for dimensionality reduction, and SMOTE method is used to balance the minority class of dataset. The experimental results proved that the model outperforms than other state-of-the-art models, with an accuracy score of 99.86%.

Why do employees hide knowledge after working hours? Linking non-working time ICT demands to deceptive knowledge hiding

PurposeEmployees may adopt deceptive knowledge hiding (DKH) due to nonworking time information and communication technology (ICT) demands. Drawing from the conservation of resources (COR) theory, this study aims to develop and test a model of deceptive knowledge hiding (DKH) due to nonworking time information and communication technology (ICT) demands.Design/methodology/approachIn total, 300 service employees have joined the three-wave surveys. Path analysis and bootstrapping methods were used to test the theoretical model.FindingsResults suggest that knowledge requests during nonworking time could deplete employees’ resources and increase their tendency to engage in DKH, whereas work recovery and emotional exhaustion mediate this relationship. In addition, employees’ work–family segmentation preferences (WFSP) were found to moderate the direct effects of nonworking time ICT demands on employees’ work recovery and emotional exhaustion and the indirect effects of knowledge requests after working hours on DKH through employees’ work recovery and emotional exhaustion.Originality/valueFirst, the findings of this study shed light on the relationship between knowledge requests during employees’ nonworking time and knowledge hiding, suggesting that knowledge hiding could occur beyond working hours. Second, drawing on COR theory, this study explored two joint processes of resource replenishment failure and depletion and how nonworking time ICT demands trigger knowledge hiding. Third, the interaction effect of individuals’ WFSP and nonworking time factors on knowledge hiding deepens the understanding of when nonworking time ICT demands may induce knowledge hiding through various processes.

Analysis of the Impact of Supply Chain Standardization Management on China’s Catering Industry

With the development of China’s social economy, catering service has become a major consumption hot spot for the public. At the same time, external factors such as information technology and consumer demand have also brought new challenges to catering enterprises, which makes China’s catering industry pay attention to supply chain management. The upgrading and transformation of the catering industry’s supply chain have effectively reduced traditional operating costs and expanded the market share. On the contrary, the market gradually eliminates those catering companies that do not pay attention to upgrading and transforming the supply chain. Those catering enterprises who are committed to upgrading the supply chain have gradually found that the role of standardized management is becoming more and more important. From the perspective of standardized management, this paper discusses the impact of supply chain standardized management on China’s catering industry by comparing domestic and foreign standardization.

Bilgi ve İletişim Teknolojisi Talepleri ile Çalışanların İyi Oluşları Arasındaki İlişkide Beş Büyük Kişilik Özelliğinin Düzenleyici Rolü: Kavramsal Bir Çalışma

As technology continues to evolve, the use of information and communication technologies in the workplace has started to increase rapidly leading to the emergence of information and communication technology demands. The COVID 19 pandemic has also had an impact on these uses and demands. Information and communication technology demands are one of the topics that have gained importance in the literature, but there is limited research on the relationship between information and communication technology demands and employee well-being, and the findings are inconsistent. This study, which examines the relationship between information and communication technology demands and employee well-being in terms of subjective well-being, psychological well-being, social well-being and workplace well-being, also draws attention to the role of the Big Five personality model within the relationship.

Investigation of engagement and performance among female and male students in technical Higher Education

ABSTRACT The present-day training domain with the greatest enrolment of students in our nation is that of technical sciences. Nevertheless, this field also witnesses one of the highest rates of dropout. In fields of Science, Technology, Engineering and Mathematics (STEM) hold great significance in the future labor market, given the constant growth in the demand for technical experts and information technology (IT) professionals. Thus, curtailing student attrition assumes particular significance. This article presents partial findings from a series of studies investigating the influence of engineering students' attitudes and commitment on academic outcomes. Our analysis places particular emphasis on the comparison of the academic achievements of male and female students.

Emerging Robust Polymer Materials for High-Performance Two-Terminal Resistive Switching Memory.

Facing the era of information explosion and the advent of artificial intelligence, there is a growing demand for information technologies with huge storage capacity and efficient computer processing. However, traditional silicon-based storage and computing technology will reach their limits and cannot meet the post-Moore information storage requirements of ultrasmall size, ultrahigh density, flexibility, biocompatibility, and recyclability. As a response to these concerns, polymer-based resistive memory materials have emerged as promising candidates for next-generation information storage and neuromorphic computing applications, with the advantages of easy molecular design, volatile and non-volatile storage, flexibility, and facile fabrication. Herein, we first summarize the memory device structures, memory effects, and memory mechanisms of polymers. Then, the recent advances in polymer resistive switching materials, including single-component polymers, polymer mixtures, 2D covalent polymers, and biomacromolecules for resistive memory devices, are highlighted. Finally, the challenges and future prospects of polymer memory materials and devices are discussed. Advances in polymer-based memristors will open new avenues in the design and integration of high-performance switching devices and facilitate their application in future information technology.

Distributed Denial of Service Attack Detection in Network Traffic Using Deep Learning Algorithm.

Internet security is a major concern these days due to the increasing demand for information technology (IT)-based platforms and cloud computing. With its expansion, the Internet has been facing various types of attacks. Viruses, denial of service (DoS) attacks, distributed DoS (DDoS) attacks, code injection attacks, and spoofing are the most common types of attacks in the modern era. Due to the expansion of IT, the volume and severity of network attacks have been increasing lately. DoS and DDoS are the most frequently reported network traffic attacks. Traditional solutions such as intrusion detection systems and firewalls cannot detect complex DDoS and DoS attacks. With the integration of artificial intelligence-based machine learning and deep learning methods, several novel approaches have been presented for DoS and DDoS detection. In particular, deep learning models have played a crucial role in detecting DDoS attacks due to their exceptional performance. This study adopts deep learning models including recurrent neural network (RNN), long short-term memory (LSTM), and gradient recurrent unit (GRU) to detect DDoS attacks on the most recent dataset, CICDDoS2019, and a comparative analysis is conducted with the CICIDS2017 dataset. The comparative analysis contributes to the development of a competent and accurate method for detecting DDoS attacks with reduced execution time and complexity. The experimental results demonstrate that models perform equally well on the CICDDoS2019 dataset with an accuracy score of 0.99, but there is a difference in execution time, with GRU showing less execution time than those of RNN and LSTM.

Assessing Study Skill Needs for Information Technology and Computer Science Students in Technical and Vocational Universities

Not a great deal is known about what study skills are essential for success in the science, technology, engineering, and mathematics' disciplines, particularly in information technology (IT) and computer science (CS) programs in the technical and vocational education (TVE) in Taiwanese higher education. Since TVE accounts for more than half of the post-secondary enrolments in the country, and with the increasing demand for IT and CS talents, we studied perceptions of the importance and competency of such skills to identify the students’ needs and demographic factors influencing them. A survey was administered to 1398 students in IT and CS programs in Taiwanese TVE universities. General skills were seen as the most important one among the study skills examined, and students felt competent using them. The needs to manage time, perform quantitative/mathematical tasks, and delegate were identified and these needs were affected by institutional quality, gender, and academic achievement. The results might be useful for further investigation in this area and guiding future plan to improve student performance in TVE.

Mathematical Modeling of Risk Management Processes in IT Companies

Today, there is a rapid increase in the demand for information technologies. This is due to many different factors, such as the increase in the amount of information in the world, the increase in the number of investments in this area in the economy. IT products are characterized by a high degree of uniqueness on their own. The article defines the main mathematical models of the risk management process in IT companies. The classification of risks in the field of information technologies is presented, their features are described. The foundations for the construction of more functional and mathematically based models of IT risk management are defined, and the shortcomings of the described methods are also noted. The main parameters of risk in IT companies are considered and their types are determined. The basis for building more functional and mathematically justified models of IT risk management is summarized, and the shortcomings of the described methods are also noted. A conclusion was made about the need to analyze the theoretical aspects of risk management and their adaptation to modern market conditions and the practical application of theoretical postulates in the management system of a business entity.

Research on the Reform of Translation Teaching for English Majors by TBLT under the Background of AI

With the continuous development of society and the changes of the times, English has gradually become one of a fundamental requirement for talents. As the cradle of cultivating talents, colleges and universities play a pivotal role in educational reform. In the new era, the development of modern information technology demands English teaching to maintain innovation and keep pace with the times. The task-based language teaching approach is used in the translation teaching for English majors in colleges and universities to explore a new mode of English teaching. In teaching, by allowing students to complete the corresponding target tasks, develop students' ability to comprehensively use information, and promote the effective cultivation of students' English translation ability, thereby improving students' English cross-cultural level and translation ability. College English teaching should prioritize the cultivation of students' practical translation ability. Therefore, based on the characteristics of task-based language teaching, artificial intelligence technology is introduced into English translation teaching for English majors to assist in completing tasks using intelligent translation, so as to realizing a new model of student-centered English teaching. Taking English translation teaching as an example, this paper discusses how to reform the translation teaching for English majors in colleges and universities under the new situation of artificial intelligence application in the field of translation.

The Paradox of Information and Communication Technology Demands at Work on Creativity

The Paradox of Information and Communication Technology Demands at Work on Creativity