Data Analysis Tools Research Articles

Comparative Analysis of Intrusion Detection Models using Big Data Analytics and Machine Learning Techniques

Traditional cyber security measures are becoming less effective, leading to rise in modern attacks. However, the ability to analyze and use massive volume of data (big data) to train anomaly based systems that can learn from experience, classify attacks and make decisions can improve prediction of attacks before they actually occur. In this study, to ensure availability, integrity, and confidentiality of information systems, predictive models for intrusion detection that use Big Data and Machine Learning (ML) algorithms were proposed. The proposed approach used a big dataset (CIC-Bell-IDS2017) to independently train three ML classifiers before and after feature selection. Big data analytics tool was also employed for feature scaling and selection in order to normalize data and select the most relevant set of features. Performance evaluation and comparative analysis were done and the results showed there were improvements in the models’ prediction accuracies.

Organizational Digital Literacy and Enterprise Digital Transformation: Evidence From Chinese Listed Companies

The importance of organizational digital literacy has come to dominate discourse on enterprise digital transformation. Drawing on Organizational Affordance Theory, we explored the relationship between three levels of organizational digital literacy—employee, senior executive, and organization—and enterprise digital transformation. Utilizing a big data analytical tool, we first probed the employee digital literacy of Chinese listed companies, then analyzed this with senior executive digital literacy and organizational hard/soft digital literacy data to generate a configuration of organizational digital literacy conditions linked with higher level digital transformation. Our findings show that attributes of organizational digital literacy (i.e., employee, senior executive and hard/soft organizational) serve as important conditions for digital transformation, but higher level digital transformations are driven by a combination of these conditions through seven types of configurations. Extending the understanding of the role of organizational digital literacy during enterprise digital transformation, our study offers insight into strategic capability requirements for embarking on successful digital transformation.

VHDLISTE: An Instructional Strategy to Cover the Additional Content beyond the Curriculum

Abstract: In current scenario of engineering education, Students must have more practical knowledge and skills required to work in the technologies that are currently used in industries though they are not the part of the curriculum. The instruction based videos help students to develop their hands on the new skills that are essential for their adaptability to new technologies. Handout is the guided document which contains the instructions to follow during the laboratory session to complete the problem statement given in the assignment. Assessment of their knowledge acquirement and skills is done through grading of assignments given to them. So in this article, VHDLISTE (Instructional Videos followed by Handout Learning – Implement, Submit, Test, and Evaluate) instructional strategy is designed and implemented for Tableau: A Visual Data Analytics Tool which is the part of the course Business Intelligence and Big Data Analytics of Final Year Computer Science and Engineering but is not covered in the syllabus. This VHDLISTE instructional strategy consists of six phases V- Instructional Videos, HDL- Handout Learning, I – Implement, S – Submit, T-Test, and E – Evaluate. In first phase V - Instructional Videos phase, students watch the instructional videos prepared by the instructor to get acquainted with the Tableau tool. In second phase HDL, students go through the lab handouts to read the instructions given for completing the lab assignment. In I – Implement phase, students implement the problem statement related to Tableau tool while test on covered topics is conducted in T-Test phase. In S – Submit, students submit the problem statement on institutional MOODLE. Instructor conducts the test on covered topic in T-Test phase. Instructor evaluates the problem statement as well as test submitted by students on institutional MOODLE in E – Evaluate phase.Learning objective (LOs) of this study is to teach the problem analysing and solving ability. These LOs are 1) Apply Filters on Dimensions and Measures for given dataset using Tableau (LO1) and 2) Apply K-means Clustering on given dataset in Tableau (LO2). The research question is - Whether the use of instructional strategy VHDLISTE is useful for learning the content beyond the curriculum? This activity is conducted for two Academic Years 2020-21, 2021-22 and 2022-23. The result of applying this strategy and perception of students are also explained. The result showed that this strategy improves the problem analysis as well as problem solving ability of students. Using t-test statistical analysis, it is found that there is significant difference in mean score between sample and overall population means for LO1 as well as LO2 for all these three years. Keywords: Learning Objectives, Handouts, Instruction based Videos, t-Test

Comparative Analysis of Intrusion Detection Models using Big Data Analytics and Machine Learning Techniques

Traditional cyber security measures are becoming less effective, leading to rise in modern attacks. However, the ability to analyze and use massive volume of data (big data) to train anomaly based systems that can learn from experience, classify attacks and make decisions can improve prediction of attacks before they actually occur. In this study, to ensure availability, integrity, and confidentiality of information systems, predictive models for intrusion detection that use Big Data and Machine Learning (ML) algorithms were proposed. The proposed approach used a big dataset (CIC-Bell-IDS2017) to independently train three ML classifiers before and after feature selection. Big data analytics tool was also employed for feature scaling and selection in order to normalize data and select the most relevant set of features. Performance evaluation and comparative analysis were done and the results showed there were improvements in the models’ prediction accuracies.

Analysis of Gestational Diabetes Mellitus (GDM) and Its Impact on Maternal and Fetal Health: A Comprehensive Dataset Study Using Data Analytic Tool Power BI

Analysis of Gestational Diabetes Mellitus (GDM) and Its Impact on Maternal and Fetal Health: A Comprehensive Dataset Study Using Data Analytic Tool Power BI

Using Big Data Analytics Tools to Predict Lawsuits <br>

Using Big Data Analytics Tools to Predict Lawsuits <br>

Data-Driven Hypothesis Generation in Clinical Research: What We Learned from a Human Subject Study?

Hypothesis generation is an early and critical step in any hypothesis-driven clinical research project. Because it is not yet a well-understood cognitive process, the need to improve the process goes unrecognized. Without an impactful hypothesis, the significance of any research project can be questionable, regardless of the rigor or diligence applied in other steps of the study, e.g., study design, data collection, and result analysis. In this perspective article, the authors provide a literature review on the following topics first: scientific thinking, reasoning, medical reasoning, literature-based discovery, and a field study to explore scientific thinking and discovery. Over the years, scientific thinking has shown excellent progress in cognitive science and its applied areas: education, medicine, and biomedical research. However, a review of the literature reveals the lack of original studies on hypothesis generation in clinical research. The authors then summarize their first human participant study exploring data-driven hypothesis generation by clinical researchers in a simulated setting. The results indicate that a secondary data analytical tool, VIADS-a visual interactive analytic tool for filtering, summarizing, and visualizing large health data sets coded with hierarchical terminologies, can shorten the time participants need, on average, to generate a hypothesis and also requires fewer cognitive events to generate each hypothesis. As a counterpoint, this exploration also indicates that the quality ratings of the hypotheses thus generated carry significantly lower ratings for feasibility when applying VIADS. Despite its small scale, the study confirmed the feasibility of conducting a human participant study directly to explore the hypothesis generation process in clinical research. This study provides supporting evidence to conduct a larger-scale study with a specifically designed tool to facilitate the hypothesis-generation process among inexperienced clinical researchers. A larger study could provide generalizable evidence, which in turn can potentially improve clinical research productivity and overall clinical research enterprise.

Quality Management System and Audit Quality: The Moderating Effect of Independent Audit Inspection in China

Research aim: This study examines the effect of quality management systems (QMS), in terms of leadership responsibility, relevant ethical requirements, human resource, engagement performance, and monitoring, on audit quality (AQ). Also, this study examines whether independent audit inspection moderates the relationship between QMS and AQ. Design/ Methodology/ Approach: A total of 414 external auditors working in Chinese accounting firms responded to the online survey questionnaires. Research finding: By using SmartPLS as a tool for data analysis, the results showed that all elements of the quality QMS have positive effect on AQ. However, it failed to establish the moderating effect of an independent audit inspection on QMS and AQ. Theoretical contribution/ Originality: This study contributes to elucidating the significance of QMS in promoting AQ, as well as shedding light on the ongoing debate regarding the impact of independent audit inspection on AQ. Practitioner/ Policy Implication: Public accounting firms and regulators should focus on improving QMS to ensure high audit quality.

Impact of Emotional Intelligence on Employee Work-Life Balance: A Study of Clinical, Non-Executive Level Employees in ABC Hospital (Pvt) Limited

The current study examines the impact of Emotional Intelligence (EI) on the Work-life Balance of Clinical, Non-Executive level employees in ABC Hospital (Pvt) Ltd. This study explored the relationship and examined the influence of those variables among non-executive level employees who work in a service Company in Sri Lanka. This research is a deductive (theory–testing) research. This research was conducted using survey research strategy and quantitative research method. Non-Executive clinical level employees of ABC Hospitals were chosen as the population of the study. A Simple random sampling technique was used calculate the sample size. Accordingly, sample size was 155 observations and used primary data as data source, data collection was done through a self-administered printed questionnaire. The number of employees who responded was 155 among 160 employees. Statistical Package for Social Science (SPSS), version 23.0 was used as the data analysis tool. The results indicate that emotional intelligence has significant direct effects on employee work-life balance. It can be concluded that self-management is the most impacted dimension of emotional intelligence in determining employee work-life balance. According to the hypotheses testing, there is a positive correlation between work-life balance and the dimensions of emotional intelligence. Parametric test including correlation and multiple linear regressions proves the results findings. There is a statistically significant relationship between emotional intelligence and the level of work-life balance. Management can take necessary actions to enhance the EI of their employees so that it will support them to have a proper work-life balance. Management needs to focus on the level of EI of their employees to enrich work-life balance to achieve higher level of productivity, commitment, and involvement.

Investigating the Factors of Green Purchase Intention on Green Cosmetics in Indonesia

Research aims to investigate the factors influencing the intention to purchase green cosmetics in Indonesia. The applied research method is quantitative and causal, utilizing a non-probability sampling technique with 300 respondents. Structural Equation Model (SEM) with Partial Least Squares (PLS) is employed as the data analysis tool. The study's findings indicate that the perception of behavioral control, epistemic value, and emotional value does not significantly influence the intention to purchase environmentally friendly cosmetic products in Indonesia. On the other hand, health awareness and environmental knowledge play a crucial role in shaping environmental attitudes. Subjective norms, environmental attitudes, functional price value, social value, and conditional value significantly impact the intention to purchase environmentally friendly cosmetic products. The implications of these findings offer insights to the cosmetics industry to align their marketing strategies with values that are more socially and environmentally oriented, aiming to enhance consumer intention to purchase green cosmetics in Indonesia.

Yüksek Öğretimde Yazılı Öğretmen Dönütünü Anlama Üzerine Bir Çalışma: İngilizce Öğretmen Adaylarının Düşünce, Duygu ve Performansları

This study aimed to explore pre-service English language teacher’s performance in revising their writing assignments based on written teacher feedback. Moreover, the participants’ perceptions and emotions were investigated in addition to their writing self-efficacy levels. A total of 15 pre-service teachers took part in the study. Data were collected through teacher written feedback, students’ drafts, an open-ended survey and a semi-structured interview with the participants. Both qualitative and quantitative data analysis tools were employed in the study. Quantitative data analysis results revealed that the participants were more successful in revising direct teacher feedback compared to indirect teacher feedback, and there was not a positive correlation between the participants’ feedback revision success and self-efficacy levels. The results of qualitative data analysis showed that the pre-service teachers were in favor of written teacher feedback and considered it a necessity for the L2 writing class. Moreover, they opted for indirect feedback and feedback on all errors. Finally, they experienced both positive and negative emotions although negative emotions were more prevalent.

The Influence of Hedonic Shopping Motivation, Fashion Involvement, and Sales Promotion on Impulse Buying in E-commerce Shopee

The marked phenomenon of the fashion industry causes a person to experience behavior by unconsciously buying something without thinking Long or often called impulse buying driven by positive emotions and motivations. In addition to this e-commerce shopee popular today often attempt to make consumer impuls buy behavior based on hedonic shopping motivation, fashion involvement, and sales promotion The objectives of this research are analyze the influence of hedonic Shopping motivation, influence fashion involving, and sales promotion on impuls buying on shopee e- commerce. This research employs a quantitative approach to examine the population of postgraduate and bachelor’s students at FEB University of Muhammadiyah Surakarta. Utilizing a purposive sampling technique, this study engaged 100 respondents meeting specific predetermined criteria. The primary data for this research were gathered through questionnaire-based data collection techniques. Smart PLS was utilized as the primary data analysis tool. The results of the analysis of research data show that: hedonic shopping motivation has a positive and significant influence on impulsive buying; fashion involvement has a positive and significant influence on impulsive buying; And sales promotion has a positive and significant impact on impulsive buying.

Assessing Student Satisfaction with Campus Canteen Services: A Descriptive Study

A canteen serves as a venue for the serving and consumption of food, where a diverse range of snacks and beverages are available for purchase. This purpose of the study was to examine student satisfaction with campus canteen services at People’s Campus. A sample of 123 randomly selected bachelor-level students was utilized, and a descriptive research design with mean as the primary data analysis tool was employed. Data were collected through a validated questionnaire. The findings revealed an overall mean rating of 3.28, indicating that the level of student satisfaction with the canteen was moderately satisfactory. These results suggested the need for addressing canteen quality to enhance service for its student customers.

Resistance and Gender in an EFL Classroom Interaction: A Critical Discourse Analysis

A classroom is not only a place for female learners’ learning and growth but also a place for enacting their knowledge, power, positioning, and resistance in their classroom interaction. As important social members, these learners bring the society-approved discourses that restrict their gendered roles in their classroom participation. Female learners, dominated by their social-historical-cognitive selves, mostly do not try to initiate a conversation or participate in that as they have to contest the status quo of male learners who particularly dominate the conversation process. Hence, they have to struggle to negotiate their position and identity by resisting the ‘boy discourses’ that delimit their equal participation. This study focuses on the reproduction of resistance and the struggle for achieving the equality dynamics of the female learners to participate in classroom discourses. Six female learners and two teachers were the research participants at a private university in Chattogram, Bangladesh. Kumaravadivelue’s (1999) critical classroom discourse analysis (CCDA), van Dijk’s (2003; 2016) socio-cognitive and Wodak’s (2009) historical-cognitive model and Braun and Clerk’s (2006) thematic analysis approach had been used here as an analytical framework and for data analysis tool. Structured focus group interviews and classroom observation were the tools used for generating data that gave the impression that female learners use both active and passive resistance that happens due to the existing micro and macro factors surrounding them. Moreover, their historical, social, and cognitive positioning and struggle for negotiating power and identity gave them the insight that the classroom served both as a learning and growing space for them. This study contributes to the budding research on female learners’ being and becoming an identity in a powerful classroom interaction that can infl uence them beyond the classroom.

ANALISIS POTENSI EKONOMI KABUPATEN SUMBAWA TAHUN 2016-2021

This study aims to determine the potential of the economic sector which can be used as a base or superior economic sector in Sumbawa Regency District. This study used a descriptive method with the type of data used was quantitative data in the form of Gross Regional Domestic Product of Sumbawa District data for 2016-2021 from all existing economic sectors. This data was obtained from published documents or archives of the Sumbawa District Central Statistics Agency. The data analysis tool used was the analysis technique of location quotient (LQ) analysis, shift share analysis, and klassen typological Analysis. Based on the results of the LQ analysis, it shows that there are seven economic sectors in Sumbawa Regency which have an LQ value greater than 1 (>1) so that they can be used as base or superior sectors in Sumbawa District, but there are only four economic sectors in Sumbawa District those in quadrant I, namely sectors that are relatively advanced and growing rapidly (developed sectors), are the agriculture, forestry and fisheries sectors; electricity and gas procurement sector; wholesale and retail trade sector, car and motorbike repair; and the government administration, defense and mandatory social security sectors. These sectors have a very large contribution in forming Sumbawa District GRDP and if managed well these sectors will continue to be growing sectors in the future.

THE INFLUENCE OF SERVICE QUALITY AND FACILITIES ON CUSTOMER SATISFACTION IN FORMING CUSTOMERS LOYALTY IN SBU FACTORY MAINTENANCE SERVICES (JPP) OF PT. PUPUK ISKANDAR MUDA

This study examined and analyzed the effect of service quality and facilities on customer satisfaction in forming customer loyalty at SBU Factory Maintenance Services (JPP) of PT Pupuk Iskandar Muda. This study used primary data obtained by distributing questionnaires to all customers, as many as 85 respondents, with 23 questions asked using five Likert scales (strongly agree-strongly disagree). The data analysis tool used was SmartPLS. The results showed that service quality significantly and positively affected customer satisfaction and customer loyalty, and facilities significantly and positively influenced customer satisfaction and customer loyalty. Meanwhile, customer satisfaction negatively but significantly affected customer loyalty. The results of hypothesis testing show that service quality and facilities directly affected customer loyalty. Meanwhile, the test results indirectly revealed that customer satisfaction partially mediated service quality on customer loyalty.

Implementation of a Business-to-Government (B2G) Sales Analytics Tool - Hermix

The public sector sales market, i.e. Business-to-Government (B2G) market is large and relevant. It is similar, yet differs in several key aspects from other markets such as retail, consumer (B2C), or Businessto-Business (B2B). B2G is huge, at 2 trillion Euro per year in Europe, but insufficiently researched and it lacks proper tools and methods. Public contracts are difficult to access and require specialized expertise and a significant initial investment. This paper explores the implementation and evaluation of an IT platform that supports and automates public sector sales, Hermix, in a large company. This study had a qualitative longitudinal approach. It consisted of 7 workshops and 2 interviews with 8 case study participants, performed over the duration of a year. It highlights the implementation steps and results. Hermix automated a set of public sector sales processes for the host company, including: tender monitoring with email notifications, opportunity qualification, and market research, i.e. the analysis of the tactical and strategic context: buyers (public authorities), budgets, competition, partnership affinities, groups of interest, trends. It uses advanced data analytics, big-data and machine learning to provide market intelligence such as governmentgraphics, firmographics, geographics and monetary segmentation. Implementing public sector sales automation tools provides direct benefits to companies, related to: cost and time efficiency, improved proposal success rates, and strategic planning optimization. Indirect benefits for companies refer to delivery quality. Data analytics tools also support overall public procurement transparency, public spending efficiency and better public governance.

A digital taxation model for Nigeria: standardizing collection through technology integration

This paper introduces a digital taxation model for Nigeria, aimed at standardizing tax collection through advanced technology integration. The model addresses the critical need for modernizing Nigeria’s tax administration to enhance efficiency, accuracy, and compliance in tax collection processes. By leveraging digital technologies, the proposed model seeks to streamline tax administration, reduce manual errors, and improve overall tax revenue management. The model advocates for the implementation of a comprehensive digital tax infrastructure, including the development of an integrated tax management system, digital payment platforms, and real-time data analytics tools. This approach emphasizes the use of application programming interfaces (APIs) for seamless interaction between tax authorities, financial institutions, and taxpayers, ensuring a unified and efficient tax collection system. Blockchain technology is proposed to enhance transparency and traceability, providing an immutable ledger for all transactions, which helps in mitigating fraud and increasing taxpayer confidence. The digital taxation model also includes automated compliance monitoring and reporting systems that utilize artificial intelligence (AI) for predictive analytics and risk assessment. These systems are designed to identify discrepancies, flag potential non-compliance issues, and provide actionable insights to both tax authorities and businesses. Additionally, the model emphasizes the importance of taxpayer education and support, advocating for user-friendly digital platforms and resources to facilitate smooth adoption and compliance. Expected outcomes of the model include increased tax revenue through improved compliance and reduced tax evasion, enhanced operational efficiency for tax authorities, and a more transparent and equitable taxation process. By aligning with global best practices and integrating cutting-edge technologies, the digital taxation model aims to transform Nigeria’s tax administration landscape, fostering a more robust and reliable financial system.

Data-Driven Decision Making in Supply Chain Management

The importance of making decisions in supply chain management (SCM) based on data has grown significantly in recent years due to the quickly changing nature of the modern corporate environment. Within the scope of this abstract, the transformational influence of data analytics on supply chain management is investigated. Particular attention is paid to the ways in which data-driven strategies improve decision-making processes, increase operational efficiency, and boost competitive advantage. The coordination of a number of operations, including as distribution, manufacturing, inventory management, and procurement, is an essential part of supply chain management. In the past, these processes were handled by the use of intuition and facts from the past. But the introduction of sophisticated data analytics tools has completely changed the way that this approach is taken. Organisations are able to improve their operations, acquire deeper insights into the dynamics of their supply chains, and more correctly estimate demand when they make use of real-time data, predictive analytics, and machine learning algorithms.

Pengaruh Iklim Etika terhadap Kinerja Karyawan

Purpose: This study aims to determine the effect of the ethical climate, which consists of collective moral sensitivity (moral awareness and empathic concern), collective moral judgment (self-focused and focus on others), and collective moral motivation on employee performance in private tertiary institutions in Bandar Lampung. Methodology/approach: This study uses primary data from the results of a questionnaire with a Likert scale. This quantitative research distributed questionnaires to 245 respondents from private universities in Bandar Lampung. The data analysis tool used was linear regression analysis with SPSS 25. Results/findings: The study's results show that collective moral sensitivity (moral awareness and empathic concern) does not affect performance, while collective moral judgment (focus on oneself and focus on others) and collective moral motivation affect performance. Conclusion: Based on the findings of this study, it is hoped that the leaders of private higher education can provide leadership and ethics training, build organizational member trust, build a culture of inclusiveness and proactivity, and improve a sense of belonging among organizational members.