cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
-
Contact Email
-
Phone
-
Journal Mail Official
-
Editorial Address
-
Location
,
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
 58   59   60   61   62 
The Impact of CSR on Brand Identification, Word of Mouth and Consumer’s Repurchase Intention in the Retailer Industry Thi Hong Nguyet Nguyen; Nguyen Khanh Hai Tran; Khoa Do; Van Dung Tran
Emerging Science Journal Vol 7, No 6 (2023): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2023-07-06-021

Abstract

This study explored and measured the influence of corporation social responsibility (CSR) on consumers' re-purchase intentions through the mediators of brand identification and word of mouth (WOM). The quantitative method was applied in the research, and there were 287 valid respondents who had purchased something from the retailer store brands. The collected data was checked for reliability, convergence, and discriminant validity among the constructs before testing the hypothesis and the theoretical research model. In particular, the Cronbach alpha reliability, exploring factor analysis (EFA), confirmatory factor analysis (CFA), and structural equation model (SEM) were used to analyze the research data under the support of SPSS and AMOS software. The results indicate that CSR has significant effects on brand identification, WOM, and consumers' re-purchase intentions. Brand identification has a positive impact on consumers' repurchase intentions, whereas WOM has not. The findings have significant contributions to the marketing theory and provide management implications for managers, especially in retail store brands. Doi: 10.28991/ESJ-2023-07-06-021 Full Text: PDF
Light-Weight Deep Learning Model for Accelerating the Classification of Mango-Leaf Disease Bahar Uddin Mahmud; Abdullah Al Mamun; Md Jakir Hossen; Guan Yue Hong; Busrat Jahan
Emerging Science Journal Vol 8, No 1 (2024): February
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-01-03

Abstract

Mango leaf diseases represent a serious threat to world agriculture, necessitating prompt and accurate detection to avert catastrophic effects. In response, this study suggests a light-weight, deep learning-based method for automatically classifying mango leaf diseases. The model is based on the original DenseNet architecture, which is well known for its effectiveness in image classification tasks. Custom layers have been added over the existing layer of the original DenseNet model. The proposed model has been compared with other existing pre-trained models. Based on comparisons, the proposed model, DenseNet78, proved to be efficient even on a relatively small dataset, where the conventional model failed. The proposed model ensured generalization across regions, disease variants, and diverse datasets of mango leaves. The results demonstrate that the fine-tuned DenseNet architecture (DenseNet78), along with an ideal growth rate, modifying block size, and a number of layers, provides optimum accuracy, with 99.47% accuracy in identifying healthy mango leaves and 99.44% accuracy in detecting various mango leaf diseases. The results also demonstrate that the model is effective in accelerating the training process because of careful comparative analysis of all the available alternatives, including the most effective combination of optimizers, learning rate schedulers, and loss functions. The study's conclusion is an automated approach for diagnosing mango leaf disease using an improved and optimized DenseNet architecture (DenseNet78). Doi: 10.28991/ESJ-2024-08-01-03 Full Text: PDF
Artificial Intelligence for Impact Assessment of Administrative Burdens Victor Costa; Pedro Coelho; Mauro Castelli
Emerging Science Journal Vol 8, No 1 (2024): February
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-01-019

Abstract

This study proposes the use of Artificial Intelligence (AI) to automatize part of the legislative impact assessment process. In particular, the focus of this study is the automatic identification of administrative burdens from legislative documents. The goal of impact assessment for administrative burdens is to apply an evidence-based approach toward compliance costs generated by regulation. Employing advanced Natural Language Processing (NLP) techniques based on a transformer architecture, a system was specifically developed and tested using Portuguese legislation. The experimental phase involved the system's ability to accurately and comprehensively identify administrative burdens. Experimental results demonstrated the system's effectiveness, showing its suitability for supporting the legislative impact assessment process by automating a time-consuming task. To the best of our knowledge, this is the first attempt concerning the use of AI for automatizing the identification of administrative burdens. The proposed system may provide governments and policymakers with a tool to speed up the legislative impact assessment process, thereby streamlining decision-making processes. Moreover, the use of AI can make the legislative impact assessment process less subjective, thus increasing its transparency and making citizens more confident about the impartiality of the process that leads to new legislation. Doi: 10.28991/ESJ-2024-08-01-019 Full Text: PDF
Crop Detection and Maturity Classification Using a YOLOv5-Based Image Analysis Viviana Moya; Angélica Quito; Andrea Pilco; Juan P. Vásconez; Christian Vargas
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-2024-08-02-08

Abstract

In recent years, the accurate identification of chili maturity stages has become essential for optimizing cultivation processes. Conventional methodologies, primarily reliant on manual assessments or rudimentary detection systems, often fall short of reflecting the plant’s natural environment, leading to inefficiencies and prolonged harvest periods. Such methods may be imprecise and time-consuming. With the rise of computer vision and pattern recognition technologies, new opportunities in image recognition have emerged, offering solutions to these challenges. This research proposes an affordable solution for object detection and classification, specifically through version 5 of the You Only Look Once (YOLOv5) model, to determine the location and maturity state of rocoto chili peppers cultivated in Ecuador. To enhance the model’s efficacy, we introduce a novel dataset comprising images of chili peppers in their authentic states, spanning both immature and mature stages, all while preserving their natural settings and potential environmental impediments. This methodology ensures that the dataset closely replicates real-world conditions encountered by a detection system. Upon testing the model with this dataset, it achieved an accuracy of 99.99% for the classification task and an 84% accuracy rate for the detection of the crops. These promising outcomes highlight the model’s potential, indicating a game-changing technique for chili small-scale farmers, especially in Ecuador, with prospects for broader applications in agriculture. Doi: 10.28991/ESJ-2024-08-02-08 Full Text: PDF
Agriculture 5.0 and Explainable AI for Smart Agriculture: A Scoping Review Siti Fatimah Abdul Razak; Sumendra Yogarayan; Md Shohel Sayeed; Muhammad Izzat Faiz Mohd Derafi
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-2024-08-02-024

Abstract

The visionary paradigm of Agriculture 5.0 integrates Industry 4.0 principles into agricultural practices. Our scoping review explores the landscape of Agriculture 5.0, emphasizing the pivotal role of Explainable AI (XAI) in shaping this domain. Guided by the Preferred Reporting Items for Systematic Review and Meta-Analysis Scoping Review, we rigorously analyzed 84 articles published from 2018 to September 2023. Our findings highlight XAI’s potential within Agriculture 5.0, recognizing its influence on intelligent farming. We propose a conceptual framework for integrating XAI, emphasizing its impact on model transparency and user trust. Despite transformative applications, existing literature often lacks XAI discussions. Our objective is to bridge this gap and provide a reference for academics, practitioners, policymakers, and educators in the field of smart agriculture that is both environmentally friendly and technologically advanced. Doi: 10.28991/ESJ-2024-08-02-024 Full Text: PDF
Preparedness for Mandatory CSR Reporting of Multinational Companies: Case of the Czech Republic Renata Skýpalová; Hana Bohušová; Milan Křápek
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-2024-08-03-013

Abstract

The way how multinational corporations integrate CSR activities into their business practices and communicate them to stakeholders can significantly impact their market position and business reputation. This paper evaluates the perceived level of preparedness for non-financial reporting associated with social, environmental, and economic CSR activities in selected multinational corporations operating in the Czech Republic. A questionnaire survey for this research was conducted between September 2021 and January 2022, targeting a specific group of multinational corporations established in EU countries and operating in the Czech Republic. As non-financial reporting is expected to be extended to a considerably large number of companies in the near future, this research has high practical relevance for stakeholders involved in decision-making processes. It is valuable for academics as well as the findings revealed statistically significant differences in the understanding of the degree of preparedness for non-financial reporting on individual CSR activities among the respondents. Doi: 10.28991/ESJ-2024-08-03-013 Full Text: PDF
Gender Differences and Stereotypes in Teacher Resilience Research Barnová, Silvia; Vochozka, Marek; Krásna, Slávka; Gabrhelová, Gabriela; Barna, Denis
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-SIED1-011

Abstract

In the present study, the issues of teacher resilience and the persistent gender stereotypes in the field are discussed. The main objective of the conducted research study was to examine the presence of gender-stereotype-confirming behavior in coping with adversity in vocational school teachers. The Connor-Davidson Resilience Scale CDRISC-25SLOVAKwas selected as the most suitable research instrument, by means of which gender differences in the participants’ (N=474) responses in its subscales were studied. The results obtained confirmed the hypothesis presuming the existence of gender differences in the achieved scores in five of the seven dimensions of the scale, and also stereotype-confirming behaviors—according to which men are rational problem solvers while women tend to apply emotion-focused coping strategies—were reported. This knowledge can be the first step towards introducing measures with the aim to provide individuals of all genders with opportunities to broaden their scale of coping strategies and promote resilience in them. Since vocational school teachers are on the periphery of researchers’ interest and no available extensive study has been focused on gender differences in teacher resilience, the research findings aim to fill the gap in the existing knowledge, provide unique data for policymakers, and create a basis for further resilience research. Doi: 10.28991/ESJ-2024-SIED1-011 Full Text: PDF
Determinants of English Language Proficiency: A Multifaceted Analysis Panomporn Vajirakachorn; Akaraphun Ratasuk; Krittiya Anuwong
Emerging Science Journal Vol 7 (2023): 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-2023-SIED2-020

Abstract

This study investigates the determinants of English language proficiency among students at Panyapiwat Institute of Management (PIM) in accordance with the Common European Framework of Reference for Languages (CEFR) standards. The determinant factors under examination encompass students' attitudes, prior English language knowledge, information-seeking behavior, satisfaction with English language learning, teachers' expertise, teacher readiness, teaching methodologies, familial support, environmental factors, and international exposure. Data were gathered through a survey administered to 469 PIM students, and the analysis employed Partial Least Squares Structural Equation Modelling. The findings revealed that five significant factors influence PIM students' English proficiency, namely their prior English language knowledge, inclination toward seeking knowledge, teachers' expertise, classroom environment, and practical language usage experiences. Additionally, the research demonstrated a noteworthy impact of students' Grade Point Average (GPA) and the time dedicated to learning English on their CEFR scores. This study contributes to the field by shedding light on the multifaceted factors influencing English language proficiency among PIM students, offering insights that can inform language education strategies and policies. It emphasizes the importance of prior knowledge, information-seeking behavior, teacher quality, classroom environment, and practical language application in enhancing English language skills. Doi: 10.28991/ESJ-2023-SIED2-020 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
Analysis of Readiness to Use the Metaverse Platform in Learning Activities Yohannes Kurniawan; Aldino E. Susandyoga; Irfan A. Kamal; Raditya Sismandrajaya; Siti Elda Hiererra; Ganesh Bhutkar
Emerging Science Journal Vol 7, No 6 (2023): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2023-07-06-016

Abstract

Metaverse technology is one of the many technological breakthroughs in education, notably in the teaching and learning process in the classroom, especially since the COVID-19 epidemic. This study aims to investigate, model, and assess the potential adoption of metaverse technology from the viewpoint of BINUS University students. The study methodology that is employed is quantitative descriptive analysis. This research used Mozilla Hub's SPOKE to create the classroom simulation. Students are asked to use a laptop web browser and a Virtual Reality (VR) headset to replicate two scenarios from the metaverse realm. The variables used are comfort, convenience, compatibility, interest, and efficacy. The findings of this research indicate that a more significant number of participants, as much as 80% than fewer respondents (20%) were interested in employing VR (the Metaverse) for online teaching and learning using headsets. The novelty in this research is that academics can find out student behavior that they prefer to study using a VR headset compared to a regular laptop by opening a web browser. This can be a special note that the use of VR headsets in learning can increase interest in learning so that it is more effective in providing teaching material. Future work for this study is the application of this metaverse technology, which still requires work and development, as it still necessitates careful planning and consideration of a few factors, including security, infrastructure availability, and user comfort. Doi: 10.28991/ESJ-2023-07-06-016 Full Text: PDF

Page 60 of 88 | Total Record : 874

 58   59   60   61   62 

Filter by Year

2017 2026


Reset
Filter By Issues
All Issue Vol. 10 No. 1 (2026): February Vol. 9 No. 6 (2025): December Vol. 9 No. 5 (2025): October Vol. 9 No. 4 (2025): August Vol. 9 No. 3 (2025): June Vol 9, No 1 (2025): February Vol. 9 No. 1 (2025): February Vol. 9 (2025): Special Issue "Emerging Trends, Challenges, and Innovative Practices in Education" Vol 8, No 6 (2024): December Vol. 8 No. 5 (2024): October Vol 8, No 5 (2024): October Vol 8, No 4 (2024): August Vol 8, No 3 (2024): June Vol 8, No 2 (2024): April Vol 8, No 1 (2024): February Vol 8 (2024): Special Issue "Current Issues, Trends, and New Ideas in Education" Vol 7 (2023): Special Issue "COVID-19: Emerging Research" Vol 7, No 6 (2023): December Vol 7, No 5 (2023): October Vol 7, No 4 (2023): August Vol 7, No 3 (2023): June Vol 7, No 2 (2023): April Vol 7, No 1 (2023): February Vol 7 (2023): Special Issue "Current Issues, Trends, and New Ideas in Education" Vol 6 (2022): Special Issue "COVID-19: Emerging Research" Vol 6, No 6 (2022): December Vol 6, No 5 (2022): October Vol 6, No 4 (2022): August Vol 6, No 3 (2022): June Vol 6, No 2 (2022): April Vol 6, No 1 (2022): February Vol 6 (2022): Special Issue "Current Issues, Trends, and New Ideas in Education" Vol 5 (2021): Special Issue "COVID-19: Emerging Research" Vol 5, No 6 (2021): December Vol 5, No 5 (2021): October Vol 5, No 4 (2021): August Vol 5, No 3 (2021): June Vol 5, No 2 (2021): April Vol 5, No 1 (2021): February Vol 4 (2020): Special Issue "IoT, IoV, and Blockchain" (2020-2021) Vol 4, No 6 (2020): December Vol 4, No 5 (2020): October Vol 4, No 4 (2020): August Vol 4, No 3 (2020): June Vol 4, No 2 (2020): April Vol 4, No 1 (2020): February Vol 3, No 6 (2019): December Vol 3, No 5 (2019): October Vol 3, No 4 (2019): August Vol 3, No 3 (2019): June Vol 3, No 2 (2019): April Vol 3, No 1 (2019): February Vol 2, No 6 (2018): December Vol 2, No 5 (2018): October Vol 2, No 4 (2018): August Vol 2, No 3 (2018): June Vol 2, No 2 (2018): April Vol 2, No 1 (2018): February Vol 1, No 4 (2017): December Vol 1, No 3 (2017): October Vol 1, No 2 (2017): August Vol 1, No 1 (2017): June More Issue