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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 1,058 Documents
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How Innovative Behavior Affects Lecturers' Task Performance: A Mediation Perspective Bastian, Adolf; Widodo, Widodo
Emerging Science Journal Vol. 6 (2022): 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-2022-SIED-09

Abstract

Objectives: Task performance is an essential determinant of organization life, including profit and non-profit organizations. Lecturers' task performance in universities is vital to realizing the goals, which include creating quality graduates and building competitiveness that promises sustainable progress for all involved stakeholders. Therefore, it is crucial to investigate lecturers' task performance by considering other relevant variables. Accordingly, this study examined Indonesian lecturers' task performance based on innovative behavior, job involvement, and organizational citizenship behavior (OCB). The study also attempted to find relevant models of innovative behavior influencing lecturers' task performance, mediated by job involvement and OCB. Methods: Questionnaires with the Likert scale were used to collect data from 230 lecturers selected using accidental sampling. The data were analyzed using descriptive and correlational techniques and structural equation modeling. Results: Innovative behavior, job involvement, and OCB significantly affected the lecturers' task performance. Besides, job involvement and OCB mediating innovative behavior affected the lecturers' task performance. However, the mediating role of job involvement was more prominent than that of OCB. Novelty: A new model of innovative behavior mediated by job involvement and OCB was developed, affecting lecturers' task performance. It is hoped that the model can trigger interesting discussions and raise new hope for task performance improvement based on innovative behavior mediating job involvement and OCB. Doi: 10.28991/ESJ-2022-SIED-09 Full Text: PDF
Does National Governance Affect the Capital Structure of Listed Firms during the COVID-19 Pandemic? Nguyen, Kim Quoc Trung
Emerging Science Journal Vol. 7 (2023): Special Issue "COVID-19: Emerging Research"
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2023-SPER-04

Abstract

This study estimates the macro-economic factors affecting the listed small and medium enterprises' capital structures in Vietnam from 2010 to 2020. The author conducts the quantitative method (generalized method of moments”GMM) with valid instrument variables to solve the endogeneity in regression models, which refers to the determinants of capital structures. Based on the trade-off theory and the pecking order theory, the author provides evidence of macro-economic factors and firm-specific factors in explanations for the capital choices of the Vietnamese firms, including national governance, inflation, COVID-19, firm age, and asset structure. In particular, this study highlights how national governance and COVID-19 influence the capital structure of small and medium enterprises in Vietnam. Doi: 10.28991/ESJ-2023-SPER-04 Full Text: PDF
Data Driven Models for Contact Tracing Prediction: A Systematic Review of COVID-19 Muthaiyah, Saravanan; Zaw, Thein Oak Kyaw; Anbananthen, Kalaiarasi Sonai Muthu; Park, Byeonghwa; Kim, Myung Joon
Emerging Science Journal Vol. 7 (2023): Special Issue "COVID-19: Emerging Research"
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2023-SPER-02

Abstract

The primary objective of this research is to identify commonly used data-driven decision-making techniques for contact tracing with regards to Covid-19. The virus spread quickly at an alarming level that caused the global health community to rely on multiple methods for tracking the transmission and spread of the disease through systematic contact tracing. Predictive analytics and data-driven decision-making were critical in determining its prevalence and incidence. Articles were accessed from primarily four sources, i.e., Web of Science, Scopus, Emerald, and the Institute of Electrical and Electronics Engineers (IEEE). Retrieved articles were then analyzed in a stepwise manner by applying Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISM) that guided the authors on eligibility for inclusion. PRISM results were then evaluated and summarized for a total of 845 articles, but only 38 of them were selected as eligible. Logistic regression and SIR models ranked first (11.36%) for supervised learning. 90% of the articles indicated supervised learning methods that were useful for prediction. The most common specialty in healthcare specialties was infectious illness (36%). This was followed closely by epidemiology (35%). Tools such as Python and SPSS (Statistical Package for Social Sciences) were also popular, resulting in 25% and 16.67%, respectively. Doi: 10.28991/ESJ-2023-SPER-02 Full Text: PDF
Deep Learning in Predicting High School Grades: A Quantum Space of Representation Costa-Mendes, Ricardo; Cruz-Jesus, Frederico; Oliveira, Tiago; Castelli, Mauro
Emerging Science Journal Vol. 6 (2022): 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-2022-SIED-012

Abstract

This paper applies deep learning to the prediction of Portuguese high school grades. A deep multilayer perceptron and a multiple linear regression implementation are undertaken. The objective is to demonstrate the adequacy of deep learning as a quantitative explanatory paradigm when compared with the classical econometrics approach. The results encompass point predictions, prediction intervals, variable gradients, and the impact of an increase in the class size on grades. Deep learning's generalization error is lower in the student grade prediction, and its prediction intervals are more accurate. The deep multilayer perceptron gradient empirical distributions largely align with the regression coefficient estimates, indicating a satisfactory regression fit. Based on gradient discrepancies, a student's mother being an employer does not seem to be a positive factor. A benign paradigm shift concerning the balance between home and career affairs for both genders should be reinforced. The deep multilayer perceptron broadens the spectrum of possibilities, providing a quantum solution hinged on a universal approximator. In the case of an academic achievement-critical factor such as class size, where the literature is neither unanimous on its importance nor its direction, the multilayer perceptron formed three distinct clusters per the individual gradient signals. Doi: 10.28991/ESJ-2022-SIED-012 Full Text: PDF
Financial Solace: Malaysian Credit Counselling and Debt Management Agency Responses to COVID-19 Challenges Ilias, Ibtisam @ Ilyana; Hammad Azizi, Nadzratun Naim; Abdul Rahman, Noraiza; Mahali, Mazlina
Emerging Science Journal Vol. 7 (2023): Special Issue "COVID-19: Emerging Research"
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2023-SPER-011

Abstract

This study evaluates the measures undertaken by the Credit Counselling and Debt Management Agency (AKPK) to assist those financially distressed due to their inability to meet their financial commitments amidst the COVID-19 pandemic. Adopting secondary analysis of qualitative data, relevant secondary data, including journal articles, annual reports, and newspaper articles, were analyzed. The study finds that measures adopted by AKPK in response to the COVID-19 pandemic include reinforcing the workforce, enhancing IT infrastructures, deploying digital platforms, using various media channels, introducing online apps, online portals, online webinars, online learning modules, and online payment facility for all debt management participants. AKPK is also entrusted with handling small and medium enterprises (SMEs) under the Small Debt Resolution Scheme. A dedicated SME Helpdesk is established to facilitate the process. AKPK's continual support to provide financial aid is reflected in its collaborative effort with the banking industry under the Financial Management and Resilience Program and the Financial Resilience Support Program. However, the government should seriously consider strengthening personal data protection laws because of AKPK's significant reliance on digital platforms. Similarly, appropriate government bodies must take quick action to address the digital divide issue and promote inclusion to reduce disparity in terms of access to online services offered by AKPK. Also, since certain individuals or SMEs with credit facilities with entities not regulated by Bank Negara Malaysia are deprived of this incentive, relevant regulators should undertake actions to provide a similar facility. This study is significant in that it provides lessons to be learned by other credit counseling and debt management agencies in adopting effective measures to enable them to adapt to the new normal. Doi: 10.28991/ESJ-2023-SPER-011 Full Text: PDF
Gender Characteristics of Individual's Linguistic Behavior in the Context of Future Translators' Professional Training Bloshchynskyi, Ihor; Bahrii, Hanna; Nanivska, Lidiia; Tsviak, Larysa; Isaieva, Ilona; Skyba, Kateryna; Pilishek, Svitlana; Moroz, Nadiia; Herasimova, Oksana; Yamkova, Valentyna; Mishchynska, Iryna
Emerging Science Journal Vol. 6 (2022): 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-2022-SIED-014

Abstract

The article seeks to investigate the gender differences of individuals in foreign language learning and reveals the peculiarities of the implementation of linguistic behaviour in the context of a gender role approach in the process of foreign language teaching to future translators. The purpose of the article is to analyze the gender differences in the implementation of future interpreters' linguistic behavior, to develop and check the program of their foreign language skills development, and to make practical recommendations for improving the professional training, taking into account the gender peculiarities. Methods of research: theoretical, empirical, psychodiagnostic, and testing methods. The study reveals the main gender differences in the teaching of both male and female students, with a focus on the peculiarities of their perception, thinking, and foreign language abilities in general. The program and practical recommendations to foreign language instructors on the foreign language ability development of future interpreters are presented in the article based on a gender approach. The results of the research indicate that gender does affect foreign language learning styles. It has been found that considerable attention should be paid to overcoming the gender gap in the educational achievements of male and female future translators. Therefore, the authors consider it appropriate to teach a foreign language in mixed groups without dividing male and female students into separate subgroups. Doi: 10.28991/ESJ-2022-SIED-014 Full Text: PDF
Mathematics and Mother Tongue Academic Achievement: A Machine Learning Approach Nunes, Catarina; Beatriz-Afonso, Ana; Cruz-Jesus, Frederico; Oliveira, Tiago; Castelli, Mauro
Emerging Science Journal Vol. 6 (2022): 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-2022-SIED-010

Abstract

Academic achievement is of great interest to education researchers and practitioners. Several academic achievement determinants have been described in the literature, mostly identified by analyzing primary (sample) data with classic statistical methods. Despite their superiority, only recently have machine learning methods started to be applied systematically in this context. However, even when this is the case, the ability to draw conclusions is greatly hampered by the "black-box" effect these methods entail. We contribute to the literature by combining the efficiency of machine learning methods, trained with data from virtually every public upper-secondary student of a European country, with the ability to quantify exactly how much each driver impacts academic achievement on Mathematics and mother tongue, through the use of prototypes. Our results indicate that the most important general academic achievement inhibitor is the previous retainment. Legal guardian's education is a critical driver, especially in Mathematics; whereas gender is especially important for mother tongue, as female students perform better. Implications for research and practice are presented. Doi: 10.28991/ESJ-2022-SIED-010 Full Text: PDF
The Role of Technology in the Learning Process: A Decision Tree-Based Model Using Machine Learning Mendonça, Yuri V. S.; Naranjo, Paola G. Vinueza; Pinto, Diego Costa
Emerging Science Journal Vol. 6 (2022): 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-2022-SIED-020

Abstract

Machine learning approaches may establish a complex and non-linear relationship among input and response variables for the assessment of the Basic Education Development Index (IDEB) database and show indicators that may contribute to monitoring the quality of education. This paper uses extensive experimental databases from public schools, consisting of a case study in Brazil, to analyze data such as the physical and technological structure of schools and teacher profiles. The research proposes decision tree-based machine learning models for predictions of the best attributes to positively contribute to IDEB. It employs a newly developed SHapley Additive exPlanations (SHAP) approach to classify input variables, so to identify variables that impact the most the final model; a non-probabilistic sample was used, composed from three official databases of 450 schools, and 617 teachers. Results show that the number of computers per student, teachers' service time, broadband internet access, investments in technology training for teachers, and computer labs in schools are the variables that have the greatest effect on IDEB. The model applied shows high prediction accuracy for test data (MSE = 0.2094 and R² = 0.8991). This article contributes to improving efficiency when monitoring parameters used to measure the quality of a teaching-learning process. Doi: 10.28991/ESJ-2022-SIED-020 Full Text: PDF
Exploiting Idioms and Proverbs of Vietnamese Regions in Teaching Mathematics in Primary Schools Hoang, Cong-Kien; Pham, Dieu-Thuy Thi; Do, Tung; Pham, Tinh Thi; Nguyen, Minh-Nguyet Thi; Vu, Quoc-Chung; Le, Duy-Cuong; Nguyen, Thuy-Chung
Emerging Science Journal Vol. 6 (2022): 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-2022-SIED-015

Abstract

Mathematics and idioms, as well as proverbs, all reflect the laws of life. At the same time, primary school children may have heard idioms and proverbs before attending school. Therefore, there are many possibilities to exploit and apply idioms and proverbs in teaching mathematics in primary schools. This study aims to identify appropriate situations and apply idioms and proverbs in different regions of Vietnam to teaching mathematics. The researchers selected 1155 expressions related to mathematics from many typical pieces of research on idioms and proverbs in Vietnam. After surveying 1822 teachers three times in many provinces and cities in all 3 regions of Vietnam: the North, the Central and the South, the researchers have classified the data according to the criteria from closed to open-ended questions. The results show a prominent level of interest (level 4/5) of all teachers participating in the survey, and there is no difference in the effectiveness in the three regions, but there is a clear difference in regions in using idioms and proverbs. Particularly, identifying situations to teach geometric and quantitative knowledge, as well as probability and statistics, allows one to apply idioms and proverbs at a high level. It is concluded that if idioms and proverbs from Vietnamese regions are appropriately selected and applied in teaching mathematics in primary schools, they will contribute to improving students' mathematical ability and preserving the national cultural heritage. Doi: 10.28991/ESJ-2022-SIED-015 Full Text: PDF
The Effects of COVID-19 on Informal Traders in Undesignated Spaces Ndhlovu, Emmanuel; Mhlanga, David
Emerging Science Journal Vol. 7 (2023): Special Issue "COVID-19: Emerging Research"
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2023-SPER-07

Abstract

The literature on COVID-19 impacts overlooks the pandemic' impact on informal traders who operate in undesignated public spaces. While studies on the impact of COVID-19 on informal traders exist, there remains little focus on how the socio-economic livelihood activities of informal traders in undesignated public spaces, such as parks, who rely on both domestic and international tourists as customers, have been impacted. This paper fills this gap by focusing on two case studies of urban public spaces in the city of Tshwane, South Africa. These spaces are Jubilee Square and Magnolia Dell Park. The study is predicated on the spatial triad framework which enables it to interrogate how the restriction on access and utilisation of public spaces during the COVID-19 lockdown impacted on the socio-economic activities of informal traders. It found that informal traders in these two parks were the most vulnerable category of traders during the COVID-19 lockdown and faced huge socio-economic and livelihood challenges. They lost their income sources and had their social networks disrupted. The article proposes social policy interventions in the governance of public spaces as part of an effort to save both lives and livelihoods in the face of a pandemic. Doi: 10.28991/ESJ-2023-SPER-07 Full Text: PDF

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