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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 803 Documents
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The Effect of EAP on Job Performance Based on Psychological Contract and Perceived Organizational Support Cai, Yinquan; Yii, Josephine Ling Chen; Pathak, Shubham
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-2024-08-05-018

Abstract

In order to study whether employee assistance programs have a significant impact on job performance, whether psychological contract and perceived organizational support play a mediating role in job performance, and thus provide practical operational strategies for relevant enterprises to propose human resource management suggestions to promote job performance, the implementation of employee assistance programs has been the subject of practical research. The findings indicate that addressing issues related to high turnover, job burnout, and absences cannot be separated from the importance of the psychological contract, perceived organizational support, and employee performance in organizational change. By applying structural equation modeling (SEM) to the data from front-line employees of several units in China, this research tested the relationships among employee assistance programs, psychological contracts, perceived organizational support, and job performance using SPSS and AMOS. The results indicate that employee assistance programs positively affect job performance; psychological contracts and perceived organizational support play a mediating role between employee assistance programs and employee job performance (JOP). Our research suggests that an employee assistance program can optimize frontline employee assistance work, build a mechanism to stimulate frontline employees' psychological contracts, and create an organizational environment full of perceived organizational support. This study innovatively uses the structural equation model for quantitative research. In addition, most previous studies on EPA were based on a single variable, psychological contract, and POS were used as the main intermediary variables to explore the mechanism of their impact on job performance so as to enhance the explanatory power of employee job performance. Doi: 10.28991/ESJ-2024-08-05-018 Full Text: PDF
Integrated Learning Models for Micro-Teaching Course Blegur, Jusuf; Ma'mun, Amung; Berliana, .; Mahendra, Agus; Alif, Muhammad Nur; Juliantine, Tite; Lumba, Andreas J. F.
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-2024-08-06-020

Abstract

The progressive world of education needs to be accelerated by fulfilling the competencies of prospective teachers who are also progressive through a series of performance tasks that are relevant to learning needs in the 21st century. This research used Analysis, Design, Development, Implementation, and Evaluation (ADDIE) to innovate an integrated learning model for a micro-teaching course. A needs analysis was conducted on 75 students, two lecturers, and 30 teachers to assess actual performance, confirm desired performance, and identify causes of performance gaps. Researchers then designed performance tasks and validated them by 10 raters, tested them on 337 students to test the outer and inner models, and tested them on 30 students, 28 lecturers, and 49 teachers to test differences. Test content validity using the Aiken-V formula and test inter-rater reliability using ICC. Meanwhile, testing the validity and reliability of the construct uses outer and inner model analysis (CB-SEM), and the difference test uses ANOVA. The content validity results prove that all task performance meets the Aiken parameters (0.75-1.00), the interrater reliability value is 0.573, and the Cronbach alpha value is 0.931. Testing the outer model proves that the loading factor task performance value ranges from 0.709-0.874, the Cronbach alpha value ranges from 0.768-0.880, the composite reliability value ranges from 0.768-0.879, the AVE value ranges from 0.580-0.649, and the discriminant validity value ranges from 0.761-0.806. The inner model test proves that the Chi-Square/df value = 2.254, RMSEA value = 0.061, SRMR value = 0.036, NFI value = 0.910, TLI value = 0.936, and CFI value = 0.948. Meanwhile, the results of the ANOVA test confirm that the Sig value = 0.098, so it can be concluded that there are no significant differences between the three sample groups regarding the model innovation results. Thus, the 25-task performance in the integrated learning model has a significant psychometric function relative to the actual situation, so it becomes one of the references that lecturers can use to improve the competency of prospective teachers in micro-teaching courses (not limited to teaching skills, analytical thinking skills, academic integrity, and transformational leadership). Doi: 10.28991/ESJ-2024-08-06-020 Full Text: PDF
An Explainable Deep Learning Approach for Classifying Monkeypox Disease by Leveraging Skin Lesion Image Data Maseleno, Andino; Huda, Miftachul; Ratanamahatana, Chotirat Ann
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-2024-08-05-013

Abstract

According to the World Health Organization's (WHO) external situation report on the multi-country outbreak of Monkeypox in 2023, from 11 countries in Southeast Asia Regions, Thailand recorded the highest reported cases, totaling 461. The ongoing Monkeypox outbreak has raised significant public health concerns due to its rapid spread across several nations. Early detection and diagnosis are imperative for effectively treating and controlling Monkeypox. Given this context, this study aimed to determine the most efficient model for detecting Monkeypox by employing interpretable deep learning techniques. This study utilizes deep learning techniques to diagnose Monkeypox based on images of skin lesions. We evaluate based on four models—convolutional neural network (CNN), gated recurrent unit (GRU), long short-term memory (LSTM), and bidirectional long short term memory (BiLSTM)—using a publicly available dataset. Additionally, we incorporate Local Interpretable Model-Agnostic Explanations (LIME) and techniques for explainable AI, facilitating visual interpretation of model predictions for healthcare practitioners. The CNN model's performance and LSTM model's performance have an accuracy of 100%, while the GRU model's performance and BiLSTM model's performance have an accuracy of 99.88% and 99.45%. Our findings demonstrate the effectiveness of deep learning models, including the suggested CNN model leveraging the pre-trained MobileNetV2 and LSTM. These models can play a pivotal role in combating the Monkeypox virus. Doi: 10.28991/ESJ-2024-08-05-013 Full Text: PDF
Comparative Analysis of ARIMA, Prophet, and Glmnet for Long Term Evolution (LTE) Base Station Traffic Forecasting Juhana, Tutun; Yuliana, Hajiar; Hendrawan, .; Iskandar, .; Musashi, Yasuo
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-2024-08-06-04

Abstract

This study evaluates the performance of three forecasting models—ARIMA, Prophet, and Glmnet—with the primary objective of equipping the telecommunication industry with effective tools for cellular traffic forecasting. These tools lay the foundation for efficient resource management, cost optimization, and enhanced service delivery. The study begins with dataset description and preparation, followed by the selection of traffic forecasting models, and concludes with performance evaluation based on metrics such as Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Symmetric Mean Absolute Percentage Error (SMAPE), Root Mean Squared Error (RMSE), and Coefficient of Determination (R²). The main contribution of this research is a comprehensive comparison of the three forecasting methods, aiding practitioners and researchers in identifying the best prediction model for specific contexts. The findings reveal that Glmnet consistently outperforms ARIMA and Prophet across all categories of traffic forecasting on the selected performance metrics. Its ability to handle complex data structures, manage multicollinearity, and deliver robust and accurate predictions makes it the preferred choice for forecasting cellular network traffic in the telecommunications domain. Doi: 10.28991/ESJ-2024-08-06-04 Full Text: PDF
Energy Price Impact on BRIC Stock Markets: A Granger Causality Analysis Pessoa, Gustavo; Ponkratov, Vadim; Philippov, David; Shvyreva, Olga; Kuznetsov, Nikolay; Elyakova, Izabella; Mikhina, Elena; Kotova, Natalya; Pozdnyaev, Andrey; Durmanov, Akmal; Bloshenko, Tatiana
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-2024-08-06-015

Abstract

Energy prices and the stock market are two of the crucial factors in the evolving landscape of global finance, particularly in major emerging economies. However, research on how energy price changes impact stock markets in BRIC countries remains limited, despite their diverse roles in global energy markets and economies. This study investigates the causal dynamics between energy prices and stock market performance in BRIC countries, aiming to uncover short-term fluctuations and long-run relationships in these major emerging economies. Utilizing daily data from 2013 to 2023, stationarity tests, cointegration analysis, and Granger causality tests are employed to examine these relationships. Key findings reveal weak evidence of a long-run equilibrium between energy prices and stock market indices, challenging previous assumptions about their cointegration. More significantly, the findings uncovered a strong unidirectional Granger causality from oil prices to all BRIC stock market indices, while gas prices show a more selective influence. Notably, no evidence of reverse causality from stock markets to energy prices was found, highlighting the exogenous nature of global energy prices in relation to BRIC stock markets. This study uniquely analyzes oil and gas price effects on BRIC stock markets, offering insights for investors and policymakers amid increasing commodity-financial market integration. Doi: 10.28991/ESJ-2024-08-06-015 Full Text: PDF
The Role of Immersive Virtual Realities: Enhancing Science Learning in Higher Education Tene, Talia; Guevara, Marco; Moreano, Gabriel; Vera, John; Vacacela Gomez, Cristian
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-SIED1-06

Abstract

Objective: This systematic review aims to map out the role of immersive technologies, specifically virtual and augmented realities (VR and AR), in enhancing learning outcomes within higher education science programs, providing a clearer understanding of their pedagogical value. Methods: Leveraging extensive database searches in Scopus and Web of Science, an initial phase of 172 articles was identified. Through a meticulous process of screening based on inclusion and exclusion criteria, this was refined to 33 important articles. These articles were further analyzed to identify distinct structural elements regarding VR and AR interventions and their effects on educational outcomes. Analysis: Each study was evaluated for its contribution to pedagogical methods, with a focus on quantifiable changes in student performance and engagement. Results: The analysis revealed that immersive technologies are being applied across various stages of the academic crossing, from introductory courses to advanced laboratory work. Particularly, 18 articles demonstrated a significant positive or increased impact on learning outcomes. Conclusions: The review confirms that VR and AR possess a transformative potential for higher education, particularly in the sciences. These technologies not only captivate students' interest but also facilitate deeper understanding and retention of complex material. The evidence suggests that VR and AR can substantially enhance the educational experience when implemented thoughtfully. Future research should aim to expand upon these findings, exploring the longitudinal impact of immersive technologies on learning and their potential to democratize education. Doi: 10.28991/ESJ-2024-SIED1-06 Full Text: PDF
Influence of Non-Economic Factors on the Formation and Development of the Design of Financial Systems Fiapshev, Alim; Travkina, Elena; Belova, Marianna
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-2024-08-05-08

Abstract

The purpose of this scientific work is to investigate the impact of non-economic factors on the design of financial systems, focusing on the concept of institutional quality, which is measured using six indices according to the World Bank's methodology. To assess this impact, we utilized data from 1996 to 2022 for a wide range of countries, grouped into five clusters based on per capita income. The comparative analysis of these country clusters revealed a direct and consistent relationship between per capita income dynamics and financial development with changes in institutional quality. It also highlighted the significant influence of this relationship on the structural features of national financial systems. The study demonstrates that institutional quality is the starting point of this entire process, determining the effectiveness of the link between financial development and economic growth through changes in the financial structure. The findings confirm the convergence of financial development levels among countries with different financial system structures and legal traditions, provided they maintain high-quality institutions. The study underscores the importance of institutional quality in minimizing the consequences of structural distortions in the financial system and addressing gaps in financial and economic development. These results are crucial for economic policymakers in developing countries and those with low per capita incomes. Doi: 10.28991/ESJ-2024-08-05-08 Full Text: PDF
Air Pollution Forecasting in a Regional Context for Sustainable Management Guayjarernpanishk, Pannarat; Chutiman, Nipaporn; Piwpuan, Narumol; Kong-ied, Butsakorn; Chiangpradit, Monchaya
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-2024-08-05-024

Abstract

The aim of this research was to develop and apply a statistical model that can be used to forecast long-term daily maximum particulate matter with a diameter of less than 2.5 microns (PM2.5) concentrations. In order to predict the daily maximum PM2.5 concentrations in the northeastern region of Thailand, the extreme value theory was analyzed, and an appropriate distribution model was identified by employing the Generalized Pareto distribution (GPD). The data of daily maximum PM2.5 concentrations during the years 2021–2023 obtained from six stations was used. These stations are located in Khon Kaen, Loei, Nakhon Ratchasima, Nong Khai, Nakhon Phanom, and Ubon Ratchathani provinces. The results of this study reveal that the GPD is appropriate based on the results of Kolmogorov-Smirnov Statistics Test. Estimating the return levels during the following return periods: 2 years, 5 years, 10 years, 25 years, 50 years, and 100 years showed that the area in the upper northeastern region, particularly Loei and Nakhon Phanom, has daily maximum PM2.5 concentrations above 500 micrograms per cubic meter. These results can also be used as information to support decision-making when conducting response planning in high-risk areas, which can be helpful for efficient resource planning and prevention actions. Doi: 10.28991/ESJ-2024-08-05-024 Full Text: PDF
Unraveling the Myths of Rural vs. Urban Academic Achievement Drivers Beatriz-Afonso, Ana; Cruz-Jesus, Frederico
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-2024-08-06-010

Abstract

The generalized migration of individuals from rural to urban areas is a global phenomenon that entails many divides, education being one of them. However, there is a lack of understanding regarding whether the factors driving higher academic achievement (AA) differ between urban and rural students. This study uses data from almost every student in Portugal who took the Portuguese and/or mathematics high school national exams. By applying OLS, the aim is to identify the AA drivers and compare these drivers between urban and rural areas. Among the key findings, variables related to academic background emerged as the strongest predictors of AA, regardless of the environment. Additionally, ICT access is insignificant in urban and rural areas, while socio-economic status does not significantly impact AA amongst rural students. These findings highlight the need for tailored interventions that address the unique challenges faced by students in different areas, with a particular focus on enhancing academic support structures to improve educational outcomes. To the best of our knowledge, this study is the first to utilize data encompassing virtually every student in an entire country to compare and understand the differences in the determinants of AA between urban and rural areas. Doi: 10.28991/ESJ-2024-08-06-010 Full Text: PDF
Using Motion-Graphic Media to Educate Higher Education Students About Depression: A Randomized Controlled Trial Chookerd, Naparat; Mettarikanon, Dichitchai; Tawanwongsri, Weeratian; Puangsri, Pavarud; Kaeophanuek, Siriwatchana; Boonpit, Veerayut; Wanchai, Adisak
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-SIED1-015

Abstract

Objective: This study aims to compare the effectiveness of motion graphics versus pamphlets for educating young adults about depression. Methods: A multicenter randomized controlled trial was conducted from April to June 2024; participants were randomly assigned to Group A (motion-graphic media) or Group B (pamphlets) in a 1:1 ratio. Pre- and post-intervention knowledge scores were collected, and satisfaction scores were collected after intervention from group A. Findings: A total of 78 participants with a median age of 19.0 years (IQR 2.0) and predominantly women (64.1%), completed pre- and post-intervention questionnaires. The median knowledge score for Group A increased from 15.0 (IQR 4.0) pre-intervention to 18.0 (IQR 3.0) post-intervention, while Group B's scores improved from 12.0 (IQR 4.0) to 16.0 (IQR 3.0). Post-intervention scores were significantly higher in Group A compared to Group B (p = 0.002). Participants in Group A also reported high satisfaction with the educational material. Novelty:This study highlights the potential of innovative media for patient education, particularly in addressing mental health issues. Long-term cohort studies are required to assess whether this approach can improve clinical outcomes and reduce the incidence of severe depression. Doi: 10.28991/ESJ-2024-SIED1-015 Full Text: PDF

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