Big Data Analytics Quality Factors in Enhancing Healthcare Organizational Performance: A Pilot Study with Rasch Model Analysis DOI Creative Commons

Wan Mohd Haffiz Mohd Nasir,

Yusmadi Yah Jusoh, Rusli Abdullah

et al.

International Journal on Advanced Science Engineering and Information Technology, Journal Year: 2024, Volume and Issue: 14(6), P. 2076 - 2083

Published: Dec. 26, 2024

Big Data Analytics (BDA) plays a pivotal role in the digital transformation of healthcare, significantly boosting organizational performance within sector. As healthcare organizations increasingly adopt BDA to leverage data-driven decision-making, understanding factors contributing quality becomes imperative. Thus, this study has proposed and developed conceptual model, pilot is part process completing model development. The instrument, which questionnaire that been designed, needs be tested for reliability. Therefore, aims evaluate refine instrument used assess practitioners’ comprehension constructs reliability items. This utilized probabilistic approach Item Response Theory (IRT), explicitly employing Rasch Measurement Model analysis enhance accuracy measurement instruments, respondents' performance, ensure survey comprised 11 64 items, were designed measure all constructs: reliability, accuracy, completeness, timeliness, format, accessibility, usability, maintainability, portability, user satisfaction, performance. collected from 20 respondents synthesized according their responses each item. analyses performed using software, specifically Winsteps. results included findings on persons distribution map person-item relationships, identification misfitting assessment unidimensionality. Ten items removed initial set due misfit, leaving 54 effectively measured confirmed was well constructed, valid, reliable actual study.

Language: Английский

Unveiling educators’ readiness to teach through Digital Media (DM): The case of South Africa DOI Creative Commons
Godfrey Chitsauko Muyambi, Mmankoko Ziphorah Ramorola

Education and Information Technologies, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 23, 2025

Language: Английский

Citations

1
Bridging Big Data Analytics Capability with Sustainability Business Performance: A Literature Review DOI Open Access
Jekaterina Novicka, Tatjana Volkova

Sustainability, Journal Year: 2025, Volume and Issue: 17(6), P. 2362 - 2362

Published: March 7, 2025

This conceptual paper aims to discuss the crucial transformation of impacts big data analytics capability (BDAC) elements on business performance using framework sustainability reporting. The authors applied a literature review, content analysis, and bibliometric analysis as core methodology for this study define key success factors BDAC development in organisation. results are based theoretical resource-based theory knowledge-based illustrate link between financial conceptualisation presented novel model. contributes by presenting reporting diamond that defines elements’ necessary integrate organisational processes.

Language: Английский

Citations

1
The AI-Powered Evolution of Big Data DOI Creative Commons
Yulia Kumar,

Jose Marchena,

Ardalan H. Awlla

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(22), P. 10176 - 10176

Published: Nov. 6, 2024

The rapid advancement of artificial intelligence (AI), coupled with the global rollout 4G and 5G networks, has fundamentally transformed Big Data landscape, redefining data management analysis methodologies. ability to manage analyze such vast varied datasets exceeded capacity any individual or organization. This study introduces an enhanced framework that expands upon traditional four Vs Data—volume, velocity, volatility, veracity—by incorporating six additional dimensions: value, validity, visualization, variability, vulnerability. comprehensive offers a novel straightforward approach understanding addressing complexities in AI era. article further explores use ‘Big D’, AI-driven, RAG-based analytical bot powered by ChatGPT-4o model (ChatGPT version 4.0). article’s innovation represents significant advance field, accelerating deepening extraction insights from large-scale datasets. will enable us develop more nuanced intricate landscapes. In addition, we proposed tools contribute evolution analytics, particularly context AI-driven processes.

Language: Английский

Citations

5
Recommendation System for Determining the Best Banner Supplier Using Profile Matching and TOPSIS Methods DOI Creative Commons
Anik Vega Vitianingsih,

Deden Firmansyah,

Anastasia Lidya Maukar

et al.

INTENSIF Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi, Journal Year: 2024, Volume and Issue: 8(2), P. 246 - 262

Published: Aug. 31, 2024

Background: Choosing a banner supplier is significant challenge for digital printing companies due to the various advantages offered by each supplier, often leading selections based on subjective aspects such as price and quality. Objective: This research aims develop system that determines best minimize production inefficiencies maximize profits comparing two calculation methods, Profile Matching TOPSIS. Methods: A quantitative study was conducted using transaction data from last six months. The parameter criteria used in this include price, quality, delivery, availability, payment terms. compares effectiveness of TOPSIS methods identifying supplier. Results: results show method superior, yielding 100% accuracy, 84% recall, 92% F1-score, outperforming method. demonstrates correct algorithm effectively provide alternative recommendations. Conclusion: indicate leads more accurate objective decisions predetermined criteria. findings suggest further should focus refining these enhance decision-making selection.

Language: Английский

Citations

4
The Impacts of Big Data Analytics and Artificial Intelligence on Marketing Strategies DOI Creative Commons

Luther Kington Nwobodo

Global journal of economic and finance research., Journal Year: 2025, Volume and Issue: 02(01)

Published: Jan. 15, 2025

The marketing sector has seen a significant transformation, particularly due to the emergence of data-driven decision-making and dominance digital platforms. This transition signifies deviation from traditional strategies, which formerly depended on more direct contact methods conventional market research techniques. As technologies have grown, they changed how we can track change customers' buying habits given us new ways connect with them. Digital platforms enhanced data provide marketers consumer insights, making challenging. A detailed literature review practical assessment analyse real prospective benefits big analytics artificial intelligence decision-making. According paper, AI may assist companies understand customer industry developments. They might then modify their for each user. Big improve target positioning, simplify marketing, educate consumers, affecting strategy. suggests creating analysis team, streamlining gathering combination, using adaptable analytical tools, customising efforts. Some issues remain this research. Data reliability group size matter. steps are unclear. For solid unambiguous results, future study should examine impact analytics, maybe particular sector. firms greatly enhance marketing.

Language: Английский

Citations

0
ON-PREMISE BIG DATA INFRASTRUCTURE: MAXIMIZING DATA SOVEREIGNTY AND PERFORMANCE DOI Open Access

Bharath Nagamalla

INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING & TECHNOLOGY, Journal Year: 2025, Volume and Issue: 16(1), P. 556 - 566

Published: Jan. 16, 2025

This article explores the evolving landscape of on-premise big data infrastructure, focusing on crucial balance between sovereignty and performance optimization.It examines transformation processing capabilities from traditional batch systems to modern real-time frameworks, highlighting growing importance governance in an increasingly regulated environment.The investigates core infrastructure components, particularly Hadoop ecosystem Cloudera enterprise features while analyzing comprehensive security frameworks essential for enterprises.The delves into implementation scaling strategies, examining technical requirements cost implications organizations deploying solutions.

Language: Английский

Citations

0
Enhancement of responsivity and self-powered on-chip LNOI integrated Bi₂Te₃ photodetector array DOI

Qiaonan Dong,

Xinxing Sun,

Tingfei YUAN

et al.

Optics Letters, Journal Year: 2025, Volume and Issue: 50(5), P. 1711 - 1711

Published: Feb. 5, 2025

The topological insulator Bi 2 Te 3 possesses an extraordinary optoelectronic property for wide-band optoelectronics device applications. In this study, we demonstrate a high-responsivity and self-powered on-chip lithium niobate on (LNOI) waveguide-integrated photodetector array operating at 1550 nm. Enhancement of responsivity is attributed to the decreased /Au contact resistance, which facilitated by electrothermal annealing. post-electrothermal annealed was demonstrated photocurrent response increased four orders magnitude, reaching as high 5.5 µA. It features photoresponsivity 60 mA/W time 10 µs. uniform performance fabricated arrays integrated with 4× multi-mode interference same LNOI photonic chips proves its potential applications in high-efficiency optical communication, computing, large-scale data processing.

Language: Английский

Citations

0
Mapping Data-Driven Research Impact Science: The Role of Machine Learning and Artificial Intelligence DOI Open Access
Mudassar Hassan Arsalan, Omar Mubin, Abdullah Al Mahmud

et al.

Metrics, Journal Year: 2025, Volume and Issue: 2(2), P. 5 - 5

Published: April 2, 2025

In an era of evolving scholarly ecosystems, machine learning (ML) and artificial intelligence (AI) have become pivotal in advancing research impact analysis. Despite their transformative potential, the fragmented body literature this domain necessitates consolidation to provide a comprehensive understanding applications multidimensional assessment. This study bridges gap by employing bibliometric methodologies, including co-authorship analysis, citation burst detection, advanced topic modelling using BERTopic, analyse curated corpus 1608 articles. Guided three core questions, investigates how ML AI enhance evaluation, identifies dominant outlines future directions. The findings underscore potential augment traditional indicators uncovering latent patterns collaboration networks, institutional influence, knowledge dissemination. particular, scalability semantic depth BERTopic thematic extraction, combined with visualisation capabilities tools such as CiteSpace VOSviewer, novel insights into dynamic interplay contributions across dimensions. Theoretically, extends scientometric discourse integrating computational techniques reconfiguring established paradigms for assessing contributions. Practically, it provides actionable researchers, institutions, policymakers, enabling enhanced strategic decision-making visibility impactful research. By proposing robust, data-driven framework, lays groundwork holistic equitable addressing its academic, societal, economic

Language: Английский

Citations

0
Assessing the impact of high-performance computing on digital transformation: benefits, challenges, and size-dependent differences DOI Creative Commons
Fernando Almeida, Edet Okon

The Journal of Supercomputing, Journal Year: 2025, Volume and Issue: 81(6)

Published: April 29, 2025

Language: Английский

Citations

0
Data-Centric Solutions for Addressing Big Data Veracity with Class Imbalance, High Dimensionality, and Class Overlapping DOI Creative Commons

Armando Bolívar,

Vicente García, R. Alejo

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(13), P. 5845 - 5845

Published: July 4, 2024

An innovative strategy for organizations to obtain value from their large datasets, allowing them guide future strategic actions and improve initiatives, is the use of machine learning algorithms. This has led a growing rapid application various algorithms with predominant focus on building improving performance these models. However, this data-centric approach ignores fact that data quality crucial robust accurate Several dataset issues, such as class imbalance, high dimensionality, overlapping, affect quality, introducing bias Therefore, adopting essential constructing better datasets producing effective Besides Big Data imposes new challenges, scalability paper proposes scalable hybrid jointly addressing overlapping in domains. The proposal based well-known data-level solutions whose main operation calculating nearest neighbor using Euclidean distance similarity metric. strategies may lose effectiveness dimensionality. Hence, achieved by combining transformation fractional norms SMOTE balanced reduced dataset. Experiments carried out nine two-class imbalanced high-dimensional showed our methodology implemented Spark outperforms traditional approach.

Language: Английский

Citations

3