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INDONESIA
Emerging Science Journal
Published by Ital Publication
ISSN : 26109182     EISSN : -     DOI : -
Core Subject : Social,
Environmental Science
Emerging Science Journal is not limited to a specific aspect of science and engineering but is instead devoted to a wide range of subfields in the engineering and sciences. While it encourages a broad spectrum of contribution in the engineering and sciences. Articles of interdisciplinary nature are particularly welcome.
Arjuna Subject : -
Articles 12 Documents
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Search results for , issue "Vol 8, No 4 (2024): August" : 12 Documents clear
Tribological Performance of Polymer Composite Modified with Calcined Eggshell Particles Post High-Temperature Exposure Sunardi Sunardi; Dody Ariawan; Eko Surojo; Aditya Rio Prabowo; Tohid Ghanbari-Ghazijahani; Cahyo Hadi Wibowo; Hammar Ilham Akbar
Emerging Science Journal Vol 8, No 4 (2024): August
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-04-03

Abstract

During operation, brake lining material rubs against the disc to generate heat. This heat could decrease the brake lining performance, such as the friction coefficient, specific wear rate, and interface temperature of the rubbing surfaces. The resulting wear debris is environmentally harmful and poses risks to human health. Therefore, this study aimed to replace the harmful material using eggshell particles as a filler in brake lining composite and enhance tribological properties. The brake lining samples were manufactured through three stages: cold compaction, hot compaction, and post-curing. The next step is the samples were subjected to a one-hour high-temperature exposure at 200°C, 300°C, 400°C, and 500°C. The results showed that the high-temperature exposure significantly affected the specific wear rate, friction coefficient, and interface temperature between the brake lining and disc. An interesting finding was that adding calcined eggshell particles in composite could improve the tribological properties up to 400°C. However, the best material’s performance resulted when the samples got an exposure temperature of 200°C. Doi: 10.28991/ESJ-2024-08-04-03 Full Text: PDF
Blockchain and AI-Driven Framework for Measuring the Digital Economy in GCC Julian Hoxha; Marsela Thanasi-Boçe
Emerging Science Journal Vol 8, No 4 (2024): August
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-04-019

Abstract

The rapid growth of the digital economy presents opportunities and challenges, particularly in the Gulf Cooperation Council (GCC) region, where economic diversification is essential. Accurate measurement of digital economic activity is crucial for developing effective policies and strategic decision-making. This study introduces a comprehensive Digital Economy Measurement (DEM) framework tailored for the GCC. The framework integrates blockchain technology for secure and transparent data management, FinGPT for advanced financial data analysis, and Conversational Agent (CA) for enhanced user interaction. The research methodology involves a step-by-step design, starting with identifying and categorizing relevant data sources, collecting data through APIs and web scraping, and utilizing smart contracts and oracles for validation and recording. The data is managed securely using decentralized storage solutions and regional nodes. We propose using FinGPT and CA to analyze data in-depth and extract valuable insights. User interaction is prioritized through CA, interactive dashboards, and natural language processing, which prioritize user interaction with interfaces tailored to GCC-specific languages and cultures. The study's contribution to the literature lies in its novel, integrated approach to measuring the digital economy in the GCC, addressing challenges related to data accuracy, privacy, and regulatory compliance. By leveraging blockchain, FinGPT, and CA, the DEM-GCC framework offers a robust and adaptable solution for understanding and fostering the region's digital economy. Doi: 10.28991/ESJ-2024-08-04-019 Full Text: PDF
Legal Mechanism for Regulating the Labor of Healthcare Workers Xeniya Kassymova; Yenlik Nurgaliyeva
Emerging Science Journal Vol 8, No 4 (2024): August
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-04-014

Abstract

Objective: This article aims to develop a mechanism for the legal regulation of the labor of healthcare workers in Kazakhstan based on comprehensive scientific issues analysis of ensuring the effectiveness of the legal regulation of employment relations, including by studying foreign experience in the countries of the Organization for Economic Cooperation and Development (OECD) and the Eurasian Economic Union (EAEU). Methods: Medical and pharmaceutical workers’ work regulations were analyzed to identify problems associated with personnel imbalance in Kazakhstan’s healthcare industry. The qualitative content analysis and the dialectical method of cognition formed the methodological basis of the study. Regulatory legal acts governing the issues of healthcare workers’ labor systems were units of analysis. Findings: The authors discovered certain flaws of legislative acts and their implementation about healthcare workers’ work. Improvement methods are proposed. Novelty:Theoretical novelty is represented by a topical approach of comprehensive analysis of the national labor legislation. Practical novelty includes proposals for the current employment legislation of Kazakhstan (unified regulation of working hours, unified regulation of employment contracts, upgrading remuneration system), including a new law draft, “Status of Medical and Pharmaceutical Workers”. Doi: 10.28991/ESJ-2024-08-04-014 Full Text: PDF
A New Concept of Specialized Standards to Improve the Quality of Higher Legal Education Sholpan Tlepina; Marat Sarsembayev; Yerbol Abaideldinov; Venera Balmagambetova; Zhanerke Zukay
Emerging Science Journal Vol 8, No 4 (2024): August
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-04-09

Abstract

This study analyzes specialized national and international legal acts and standards that enjoy national and international recognition and are relevant to ensuring the appropriate quality of higher legal education in Kazakhstan. Applying methods of logical and legal analysis, a global approach to comparing the practices of legal education within the country and abroad, the authors offer specific recommendations for improving specific standards of Kazakh legislation on education, namely, the adoption of the draft law “On Higher Education” in the republic; the introduction of the Socratic method in the lecture and educational process, creative vacations as a special type of professional development at law faculties of universities; the use of digital artificial intelligence tools at all stages of law students’ education; providing more practical training; and significant restructuring of the knowledge verification system in exams. It is concluded that improving the quality of legal education is necessary for training highly qualified lawyers for legal practice, and lawyers with an anti-corruption legal consciousness. The novelty of this study is determined by its unique thematic focus, since it concerns an unexplored domain of specialized legal norms in the legal education sector of Kazakhstan. In addition, this study is novel as it is the first study in the history of the Republic in terms of improving higher legal education with the help of legislative and international legal norms. The practical significance of this study lies in the regulations and practices proposed for implementation. Doi: 10.28991/ESJ-2024-08-04-09 Full Text: PDF
Augmented Reality in Natural Sciences and Biology Teaching: Systematic Literature Review and Meta-Analysis António Faria; Guilhermina Lobato Miranda
Emerging Science Journal Vol 8, No 4 (2024): August
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-04-025

Abstract

This article presents the results of a systematic literature review followed by a meta-analysis of studies on the use of Augmented Reality (AR) in the teaching and learning of Natural Sciences and Biology, among primary and secondary school students. The variables considered were the effects on student learning and motivation, as well as other variables like students understanding and students’ perception of the cognitive load. The teaching contexts and strategies used in association with AR were also considered. The PRISMA methodology was used in articles published between 2010 and 2023, in EBSCO, Science Direct, Scopus, Springer Link, Taylor & Francis and Web of Science databases. Seven hundred and twenty-one articles (721) were found, which, after applying the inclusion and exclusion criteria, were reduced to 15. The results showed that, in most studies, AR associated with certain teaching strategies and using a quasi-experimental research methodology produced better results in learning and student motivation and other variables such as student understanding and memorization (from Bloom's taxonomy), and perception of cognitive load. The overall analysis of the data allowed us to observe a strong effect size value (d = 1.13 [0.39;1.86]) in favour of the experimental group regarding learning and a moderate effect on motivation when using AR (d = 0.52 [0.30;0.74]). The same occurred with other variables studied where students obtained better results, which translated into a small or medium effect size. For example, in the perception of cognitive load, the effect size was d= 0.73. Doi: 10.28991/ESJ-2024-08-04-025 Full Text: PDF
Visualization and Analysis Method of Defect Manifestation in Electromechanical Equipment Elena Abidova
Emerging Science Journal Vol 8, No 4 (2024): August
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-04-04

Abstract

This study focuses on the problem of diagnosing electromechanical equipment and aims to prevent its failures by timely detecting hidden signs of defects in diagnostic signals. This paper considers the possibility of improving systems whose equipment monitoring relies on measuring and analyzing the diagnostic signal of vibration or motor current. Fourier series decomposition for processing complex signals is not always effective because the contribution of harmonics reflecting the specific effect of the defect is less than that of non-specific harmonics and is comparable to the influence of noise. It has been proposed to apply the singular spectral analysis method for visualizing and analyzing the regularities of defect manifestations. It is reasonable to supplement the classical algorithm of this method by comparing the analyzed eigenvalue spectrum corresponding to the operating condition. Detection of hidden defects for the first time involves analyzing initial data projections in the directions of the singular basis that reflect deviations under the defect influence. Numerical and field experiments confirm the possibility of analyzing comparatively weak generations essential for equipment condition identification. The experiments demonstrate the opportunity for timely defect detection due to preprocessing when the probability of defect detection using the frequency method is close to zero. Thus, the approach to timely detection of equipment defects and making adequate decisions to manage its condition is justified. Doi: 10.28991/ESJ-2024-08-04-04 Full Text: PDF
Driving Digital Transformation: How Transformational Leadership Bridges Learning Agility and Digital Technology Adoption in MSMEs Chwen-Li Chang; Edgar Octoyuda
Emerging Science Journal Vol 8, No 4 (2024): August
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-04-020

Abstract

Objectives: The utilization of technology within an organization is believed to enhance its effectiveness and efficiency. To reap the benefits of technology, MSMEs must adopt digital technology innovation. Individuals and its capabilities within the organization play a significant role in digital technology innovation adoption. This study aims to examine the nexus between learning agility, transformational leadership, and adoption to digital technology innovations. Methods: This study examines the hypotheses involving 203 employees of MSMEs utilizing PLS-SEM. Results: PLS-SEM results show that learning agility and transformational leadership affect digital technology innovation adoption. Accordingly, transformational leadership mediates the connection between learning agility and the adoption of digital technology innovations. Novelty:This research has implications for organizations in adopting digital innovation, where organizations can optimize individual learning agility and utilize transformational leadership styles to persuade employees to adopt digital technology innovation. Furthermore, this research lies in its comprehensive examination of how transformational leadership can amplify the effects of individual learning agility, thereby fostering a more conducive environment for digital innovation within MSMEs. In addition to a comprehensive discussion, this study provides both theoretical and practical guidelines and provides a thorough examination of both aspects. Doi: 10.28991/ESJ-2024-08-04-020 Full Text: PDF
Digital Collaboration Models for Empowering SMEs: Enhancing Public Organization Performance R. Luki Karunia; Edi Yanto; Johan Hendri Prasetyo; Erfi Muthmainah; Lely Hiswendari; Prima Setiawan; Muhammad Aulia Putra Saragih
Emerging Science Journal Vol 8, No 4 (2024): August
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-04-015

Abstract

This study aims to examine the effectiveness of SiBakul Jogja, a digital platform initiated by the government in Yogyakarta Province, in supporting small businesses and fostering collaboration among various stakeholders. Through interviews and research analysis, we investigate the mechanisms through which SiBakul Jogja facilitates small business growth and innovation. The findings reveal that SiBakul Jogja serves as a comprehensive resource hub for small businesses, offering assistance in record-keeping, advisory services, and fostering partnerships for innovation. Collaboration among government entities, businesses, academics, and the media plays a crucial role in enhancing the platform's impact. Positive outcomes include job creation and improved access to financial resources. However, challenges such as digital skills shortages and internet connectivity issues persist. The novelty of this study lies in its examination of SiBakul Jogja's collaborative approach in alignment with principles of new public service, contributing to improved public service delivery and economic growth. Addressing these challenges collectively presents an opportunity to leverage SiBakul Jogja's potential to significantly boost the local economy. Through effective teamwork and organizational strategies, digital support for small businesses can be optimized, fostering economic growth and resilience. Doi: 10.28991/ESJ-2024-08-04-015 Full Text: PDF
Adopting ISO 20022: Opportunities, Challenges, and Success Factors for Corporations in Payment Processing João Constantino; Henrique São Mamede; Miguel Mira da Silva
Emerging Science Journal Vol 8, No 4 (2024): August
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-04-010

Abstract

This research explores the adoption of ISO 20022, a standard that corporations can leverage to instruct payments to their partner financial institutions. Due to the complexity and case-specific variables involved, the adoption process may be complex and require significant effort from financial institutions and customers over an extended period. This research analyzes the opportunities and challenges for corporate users posed by ISO 20022 and identifies the success factors that must be considered during the adoption process. The research key findings indicate that an implementation approach incorporating flexibility, custom extensions, the use of a markup language for creating and managing messages, pilot testing, and user feedback can be an effective adoption model for ISO 20022. Design Science Research Methodology is employed in designing, building, and evaluating a solution proposal to develop a structured, customized, and flexible solution complying with the ever-changing requirements and landscape. This research contributes to the payment processing field by providing a comprehensive adoption model for ISO 20022 that considers critical factors and challenges. The proposed customized and flexible solution can assist corporations in successfully adopting ISO 20022 and contribute to creating a common language and model for payment data worldwide. The initiative's success depends on the effective adoption by all players, including corporations. Doi: 10.28991/ESJ-2024-08-04-010 Full Text: PDF
Analyzing Socio-Academic Factors and Predictive Modeling of Student Performance Using Machine Learning Techniques Romel Al-Ali; Khadija Alhumaid; Maha Khalifa; Said A. Salloum; Rima Shishakly; Mohammed Amin Almaiah
Emerging Science Journal Vol 8, No 4 (2024): August
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-04-05

Abstract

Understanding the factors that influence student performance is crucial for improving educational outcomes. Thus, this study aims to examine the impact of socio-economic and psychological factors on student performance, less is known about how students' personal attitudes and behaviors across different departments and activities correlate with their academic success. This study employs exploratory data analysis (EDA) to identify trends and relationships within the dataset. Machine learning techniques, such as K-means clustering and Long Short-Term Memory (LSTM) networks, are utilized to model and predict student performance based on their reported behaviors and preferences. The dataset is reduced using Principal Component Analysis (PCA) to enhance the clustering process. The findings suggest significant variations in academic performance based on departmental affiliation, gender, and engagement in certification courses. The LSTM model achieved an accuracy of 91% on the test set, demonstrating substantial predictive capability. However, the classification report reveals that while the model was highly effective in identifying the majority class (label 1), achieving a precision of 91% and a recall of 100%, it failed to correctly predict any instances of the minority class (label 0). The insights from this study could help educators tailor interventions to address the specific needs of students based on their behaviors and departmental affiliations, leading to more personalized education strategies and potentially improving academic outcomes. Doi: 10.28991/ESJ-2024-08-04-05 Full Text: PDF

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