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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 874 Documents
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Framing Assessment Questions in the Age of Artificial Intelligence: Evidence from ChatGPT 3.5 Farooqui, Mohammad Owais; Siddiquei, Mohd Imran; Kathpal, Shashank
Emerging Science Journal Vol 8, No 3 (2024): June
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-03-09

Abstract

With the rise of artificial intelligence (AI), higher education faces a significant challenge in learning assessment. The emergence of tools like ChatGPT raises concerns regarding the potential for cheating and the reliability of assessment outcomes. This paper aims to address these concerns by proposing a methodology for framing questions that effectively measures learning outcomes while reducing the risk of AI-enabled cheating. To achieve this objective, we employ a methodological approach that involves getting responses from ChatGPT 3.5 to various question prompts across different domains. These responses are then evaluated by faculty members specializing in management education. Through this process, we aim to identify question-framing strategies that effectively assess learning outcomes while minimizing susceptibility to AI Cheating. Our analysis reveals several key findings. Certain question Types (Decision Making, Recent Events, and Experiential Learning) demonstrate greater resilience against AI-generated responses, indicating their potential effectiveness in assessing student learning. This study offers original insights into the challenges and opportunities associated with learning assessment in the context of AI integration. The paper tries to provide valuable guidance for Policymakers, educators & students seeking to enhance the integrity and reliability of their assessment practices. Doi: 10.28991/ESJ-2024-08-03-09 Full Text: PDF
An Integrated Framework for Addressing the Challenges and Strategies of Technology Adoption: A Systematic Review Omar Ali; Peter A. Murray; Ahmad Al-Ahmad; Luay Tahat
Emerging Science Journal Vol 8, No 3 (2024): June
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-03-025

Abstract

While the rapid growth of information technology (IT) adoption has not lessened, insufficient attention has been directed towards the major themes and sub-themes of IT adoption challenges. Consequently, this study consists of a systematic literature review of the challenges of technology adoption based on a total of 235 peer-reviewed articles from the business and management literature between 2012-2022. Our longitudinal study provides an integrated framework for matching IT challenges to organizational strategies for transforming IT practices and processes. The results of the review broaden scholarly understanding of the importance of strategic IT agility, the need to keep pace with competitive information systems and IT environments. The findings enhance understanding of the pre-change and post-change processes of IT adoption, expanding knowledge on adoption success and organizational strategies for achieving IT strategic agility. Three key contributions include closing gaps not explored in comparative studies, adopting a unified approach with an integrated research model, and strategies to enhance an organization's absorptive IT capacity and agility. Doi: 10.28991/ESJ-2024-08-03-025 Full Text: PDF
Synthesis and Characterization of Hybridfiber from Gelatin Modified by PVACOS Using Coaxial Electrospinning Techniques as an Advanced Medical Textile Material Siti Fatimah; Sarto Sarto; Moh. Fahrurrozi; Budhijanto Budhijanto
Emerging Science Journal Vol 8, No 2 (2024): April
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-02-022

Abstract

The synthesis of hybrid fiber based on bovine bone gelatin combined with polyvinyl alcohol-chitosan-oxidized sucrose (PVACOS) has been successfully carried out using the coaxial electrospinning technique. The presence of oxidized sucrose can improve the diameter and the tensile strength of hybrid fibers due to the formation of new covalent bonds. The combination of gelatin with PVACOS material aims to increase the strength of the hybrid fiber so that it has better tensile strength characteristics and improves the diameter of the resulting hybrid fiber. The characterization of the resulting material was tested using FTIR, SEM, EDX, XRD, and TGA. Based on FTIR analysis, there is an increase in absorption intensity in the 2900 cm-1 – 3000 cm-1 band, which indicates the occurrence of covalent bond interactions so that it can increase the bond strength between materials with the performance of crystalline materials. Apart from that, the morphological structure of the hybrid fibers was also investigated using scanning electron microscopy (SEM), and the resulting fiber diameter for Ge-Ch, Ge-Ch-PVA, Ge-PVACOS 3%, and Ge-PVACOS 5%, respectively, was 0.4049 µm. 0.3735 µm, 0.3388 µm, and 0.3206 µm. The tensile strengths of hybrid fiber for Ge-PVACOS 3% and Ge-PVACOS 5%, respectively, are 39.91935 N/m2 and 76.12507 N/m2. Statistical tests show that the concentration of oxidized sucrose has a significant influence on hybrid fiber performance. The significance values for diameter and tensile strength are 0.0486 and 0.0325, respectively. According to this performance, the Ge-PVACOS hybrid fiber is recommended as a material for advanced medical textiles. Doi: 10.28991/ESJ-2024-08-02-022 Full Text: PDF
Mobile Device Forensics Framework: A Toolbox to Support and Enhance This Process Bruno M. V. Bernardo; Henrique S. Mamede; João M. P. Barroso; Vítor M. P. D. dos Santos
Emerging Science Journal Vol 8, No 3 (2024): June
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-03-011

Abstract

Cybercrime is growing rapidly, and it is increasingly important to use advanced tools to combat it and support investigations. One of the battlefronts is the forensic investigation of mobile devices to analyze their misuse and recover information. Mobile devices present numerous challenges, including a rapidly changing environment, increasing diversity, and integration with the cloud/IoT. Therefore, it is essential to have a secure and reliable toolbox that allows an investigator to thwart, discover, and solve all problems related to mobile forensics while deciphering investigations, whether criminal, civil, corporate, or other. In this work, we propose an original and innovative instantiation of a structure in a forensic toolbox for mobile devices, corresponding to a set of different applications, methods, and best practice information aimed at improving and perfecting the investigative process of a digital investigator. To ensure scientific support for the construction of the toolbox, the Design Science Research (DSR) methodology was applied, which seeks to create new and unique artifacts, drawing on the strength and knowledge of science and context. The toolbox will help the forensic investigator overcome some of the challenges related to mobile devices, namely the lack of guidance, documentation, knowledge, and the ability to keep up with the fast-paced environment that characterizes the mobile industry and market. Doi: 10.28991/ESJ-2024-08-03-011 Full Text: PDF
Enhancing Efficiency: The Impact of Cloud Computing Adoption on Small and Medium Enterprises Performance Abdalla, Reem A.; Ramayah, T.; Sankar, Jayendira P.; Hidaytalla, Lamya A.; John, Jeena Ann
Emerging Science Journal Vol 8, No 6 (2024): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-06-017

Abstract

This study investigated the factors influencing cloud computing adoption (CCA) and its impact on organizational performance (OP) among SMEs employees in Bahrain. The study used an online survey approach, which includes Likert scale questions to assess attitudes and views, multiple-choice questions for categorical data, and open-ended questions to obtain qualitative insights. The target audience comprises 300-350 small and medium-sized enterprises (SMEs) in Bahrain currently utilizing cloud computing technology, and 314 useful responses were received. A mixed two-step sampling technique was initiated by convenience sampling. Then, snowball sampling was used to guarantee the inclusion of various SME categories, thus ensuring representativeness. The measurements are derived from validated instruments used in academic research, with the questionnaire incorporating elements adapted from the studies conducted. Participants' responses to the Likert scale are analyzed using SmartPLS 4 to understand their perspectives. Full collinearity was used to assess common method bias, and VIF values below 3.3 indicated no bias. The measuring model's validity and reliability were evaluated by loadings, AVE, CR, and discriminant validity tests (HTMT), which ensured all constructs fulfilled thresholds. Path coefficients, standard errors, t-values, and p-values were used to evaluate the structural model using 10,000-sample bootstrapping. The research findings indicate that both Perceived Ease of Use (PEU) and Perceived Usefulness (PU) have a substantial impact on Cloud Computing Adoption (CCA), which in turn improves the performance of Bahraini SMEs. PEU and PU directly impact CCA while indirectly improving Organizational Performance (OP) by increasing cloud computing usage. These findings emphasize the importance of user-friendly and beneficial cloud solutions in increasing cloud computing adoption and enhancing business outcomes for SMEs. Doi: 10.28991/ESJ-2024-08-06-017 Full Text: PDF
The Impact of Motivation on MOOC Retention Rates: A Systematic Review Alj, Zakaria; Bouayad, Anas
Emerging Science Journal Vol 8 (2024): Special Issue "Current Issues, Trends, and New Ideas in Education"
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-SIED1-08

Abstract

This systematic review investigates the effectiveness of motivational strategies on learner engagement and retention rates in Massive Open Online Courses (MOOCs). Adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we analyzed 140 studies published between 2014 and 2023 from key academic databases. The objective was to identify and evaluate motivational strategies that significantly reduce MOOC dropout rates. Our findings reveal that personalized learning, interactive content, and peer collaboration are strongly correlated with increased learner engagement and persistence. These strategies align well with learners' intrinsic goals, enhancing their educational experience and adherence to courses. The review also identifies gaps, such as the need for longitudinal studies and culturally tailored motivational strategies, offering a refined agenda for future research in MOOC education. This study contributes to the field by systematically synthesizing existing research, providing new insights into effective educational strategies, and highlighting areas for improvement in MOOC design and implementation. Doi: 10.28991/ESJ-2024-SIED1-08 Full Text: PDF
Corporate Donations in the Context of Covid-19: Insights on Trust and Policy Innovation Opportunities Victorino, Guilherme
Emerging Science Journal Vol 8, No 5 (2024): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-05-010

Abstract

This study aims to investigate the determinants of corporate donations during the initial phase of the Covid-19 pandemic, focusing on the Portuguese context. It explores the interplay between pandemic-related factors, corporate structures, recipient profiles, and media coverage on the levels of corporate donations. In the absence of publicly available data, a comprehensive database of corporate donations was constructed by analyzing over six thousand news pieces from various media sources between March and May 2020. The database comprises 1171 donations from 709 different institutions. The relationship between corporate donations and multiple variables was examined, including the epidemiological progression of the pandemic, corporate ownership structures, recipient characteristics, and media coverage. Our analysis reveals that during the initial wave of the Covid-19 pandemic in Portugal, corporate donations were predominantly made by large companies, primarily directed toward their local regions. Notably, nearly 93% of all donations were allocated to the National Health System. PPEs and hospital equipment were the preferred donation items among the contributing companies. These findings shed light on the factors influencing corporate donation behavior during emergency situations and provide valuable insights into trust levels within the healthcare system. This study contributes to the existing literature by offering a unique exploration of corporate donation behavior during the Covid-19 pandemic, specifically in Portugal. The comprehensive dataset and findings provide novel insights into the factors shaping corporate donation decisions during crises. Doi: 10.28991/ESJ-2024-08-05-010 Full Text: PDF
Leveraging Feature Sets and Machine Learning for Enhanced Energy Load Prediction: A Comparative Analysis Almeida, Fernando Pedro Silva; Castelli, Mauro; Côrte-Real, Nadine
Emerging Science Journal Vol 8, No 6 (2024): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-06-01

Abstract

Accurate cooling consumption forecasts are crucial for optimizing energy management, storage, and overall efficiency in interconnected HVAC systems. Weather conditions, building characteristics, and operational parameters significantly impact prediction accuracy. Since meteorological conditions highly influence cooling demand, leveraging external air data and user metrics offers a promising approach to estimate a building's hourly cooling energy usage. This study addresses the gap in existing research by comprehensively analyzing the performance of various machine learning algorithms, including ensemble learning and deep learning models, to improve prediction accuracy. By leveraging weather conditions, building characteristics, and operational parameters, we aim to predict cooling consumption across multiple systems (Cooling Ceiling, Ventilation, Free Cooling, and Total Cooling). Data from four weather stations, encompassing diverse features relevant to the European Central Bank (ECB) building's cooling consumption in Frankfurt, were employed. Our methodology includes the use of K-Nearest Neighbor, Decision Tree, Support Vector Regression, Linear Regression, Random Forest, Gradient Boosting, XGBoost, Adaboost, Long-Short-Term Memory, and Gated Recurrent Unit. Models. The results consistently demonstrate the superiority of the Random Forest model across different weather stations and feature sets. This model achieved a Mean Squared Error of approximately 0.002-0.003, Mean Absolute Error of around 0.031-0.034, and Root Mean Squared Error of about 0.052-0.069. These findings contribute to improved building cooling load management, promoting insights into optimal energy utilization and sustainable building practices. Doi: 10.28991/ESJ-2024-08-06-01 Full Text: PDF
The Impact of Artificial Intelligence on Digital Marketing: Leveraging Potential in a Competitive Business Landscape Hendrayati, Heny; Achyarsyah, Mochamad; Marimon, Frederic; Hartono, Ulil; Putit, Lennora
Emerging Science Journal Vol 8, No 6 (2024): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-06-012

Abstract

This study aims to thoroughly investigate how Artificial Intelligence (AI) is strategically integrated into digital marketing practices and its consequential effects on Indonesia’s fiercely competitive business environment. Employing a quantitative research approach, this study meticulously examines Indonesian enterprises’ prevailing strategies for AI utilization. The research method employed in this study is quantitative, with the unit of analysis being Indonesian companies. The sample size comprises 100 companies selected through the stratified random sampling technique. Analysis of the data is conducted using the SPSS statistical package. Through detailed analysis of survey data and advanced statistical techniques, the research reveals a significant positive correlation between the integration of AI in digital marketing and improved marketing effectiveness. The study highlights a noticeable increase in customer engagement metrics and noteworthy enhancements in conversion rates among businesses proficient in leveraging AI technologies, further reinforcing this correlation. Additionally, the findings suggest that companies embracing AI demonstrate significantly heightened adaptability to the constantly evolving market dynamics, strengthening their competitive positioning. These insightful discoveries underscore the critical importance of harnessing AI’s transformative capabilities within digital marketing strategies to sustain and bolster a competitive edge in the marketplace. Furthermore, the study discusses its contributions to existing knowledge and provides practical implications for marketers and business policymakers in Indonesia. Doi: 10.28991/ESJ-2024-08-06-012 Full Text: PDF
M-Learning and Experiential Learning in Vocational Education Luptáková, Iveta D.; Hanuliaková, Jana; Žido, Lukáš; Bartoš, Pavel
Emerging Science Journal Vol 8 (2024): Special Issue "Current Issues, Trends, and New Ideas in Education"
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-SIED1-017

Abstract

The aim of our research was to investigate the impact of the use of mobile devices in mobile technology (MT)-enabled experiential learning (EL). Methods/Analysis: The basis of the research was an experiment. Quantitative data included pretest and post-test results of two groups of students (ELs and regular education students). Qualitative data consisted of individual analysis of a final questionnaire composed of 37 items, some of which were open-ended. A 5-point Likert scale was used for evaluation, and some questions were open-ended. Findings: The results showed that the average knowledge gained in the EL group's post-test increased compared to the regular class. We found that after the photographing/note-taking phase, students with the ability to use mobile devices generally lost interest in further observation. We also found that both groups had great difficulty in the question design and comparison sections, in finding answers to the prepared questions. Novelty/Improvement:it became apparent that the teaching process needed to be modified. The photo-taking phase should be done after close observation so that the sensory experience is not replaced by mobile devices. The comparison phase did not show a significant result in any of the observed viewpoints and can be omitted. The sensory experience, sound recording, requires some modifications, more effectively applied in the classroom environment, as ambient noise was a problem in the teaching process. Doi: 10.28991/ESJ-2024-SIED1-017 Full Text: PDF

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