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All Journal International Journal of Electrical and Computer Engineering JOIV : International Journal on Informatics Visualization ASEAN Marketing Journal
Yazrina Yahya
Faculty of Information Science & Technology, Universiti Kebangsaan Malaysia
Computer Science & IT Electrical & Electronics Engineering Social Sciences

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E-travel Adoption by Small Travel Enterprises (STEs): An Initial Study in Indonesia and Malaysia Pujani, Vera; Yahya, Yazrina; Alfitman, Alfitman; Nazir, Refdinal
ASEAN Marketing Journal Vol. 7, No. 1
Publisher : UI Scholars Hub

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Abstract

This paper aims to investigate e-travel adoption of tourism industries in Indonesia and Malaysia particularly by STEs. The qualitative research was undertaken using case analysis from in-depth interviews of 10-STEs as intial study both in Indonesia and Malaysia. The finding result of e-travel adoption by STEs in a cross-cultural study was identified from the findings present in the initial study based on personal, organizational and website characteristics. The majority of personal characteristics were relatively similar in both countries. However, few differences are present in organizational and website characteristics. E-travel adoption in both countries is influenced by the business experiences of owners/managers, various technological aspects, and the nature of use and benefits. The following study, the user-based survey would be undertaken to complete The e-travel adoption model in Indonesia and Malaysia.
Technologies on Intelligent Financial Risk Early Warning in Higher Education Institutions: A Systematic Review Chao, Yu; Elias, Nur Fazidah; Yahya, Yazrina; Jenal, Ruzzakiah
JOIV : International Journal on Informatics Visualization Vol 8, No 3 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.3.1536

Abstract

Financial risk early warning (FREW) is critical for developing Higher Educational Institutions (HEIs). This review uses the Systematic Literature Review (SLR) method to discuss the current research status, leading causes, early warning techniques, and algorithms of financial risk management in HEIs. Based on the WoS database, 139 articles meeting the research criteria were selected from 451 relevant literature for in-depth analysis. The results show that the current research on financial risk management in HEIs mainly focuses on developing risk identification, assessment, and early warning models. The primary sources of university financial risk include the instability of fundraising and distribution, decreased financial allocation, and intensified market competition. In response to these risks, scholars have proposed various early warning models and technologies, such as univariate, multivariable, and artificial neural network models, to predict and manage these risks better. In terms of methodology, this review provides a comprehensive perspective on the study of university financial risk through quantitative and qualitative analysis. This study reveals this field's main research trends and gaps through literature screening and cluster analysis. Finally, this study discusses the practical significance of financial risk management in HEIs, highlighting its role in the stability and growth of these institutions. It suggests future research directions, especially in improving the accuracy and applicability of the Early Warning System (EWS), to further enhance the financial stability of HEIs. This literature review has crucial theoretical value for the academic community and provides practical guidance for HEI administrators.
A systematic review of heuristic and meta-heuristic methods for dynamic task scheduling in fog computing environments Talhouni, Hamed; Ali, Noraida Haji; Yunus, Farizah; Atiewi, Saleh; Yahya, Yazrina
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i6.pp5986-6000

Abstract

The distributed fog node network and variable workloads make task distribution difficult in fog computing. Optimizing computing resources for dynamic workloads with heuristic and metaheuristic algorithms has shown potential. To address changing workloads, these algorithms enable real-time decision-making. This systematic review examines heuristic, meta-heuristic, and real-time dynamic job scheduling strategies in fog computing. Static methods like heuristic and meta-heuristic algorithms can help modify dynamic task scheduling in fog computing situations. This paper covers a current study area that stresses real-time approaches, meta-heuristics, and fog computing environments' dynamic nature. It also helps build reliable and scalable fog computing systems by spotting dynamic task scheduling trends, patterns, and issues. This study summarizes and analyzes the latest fog computing research on task-scheduling algorithms and their pros and cons to adequately address their issues. Fog computing task scheduling strategies are detailed and classified using a technical taxonomy. This work promises to improve system performance, resource utilization, and fog computing settings. The work also identifies fog computing job scheduling innovations and improvements. It reveals the strengths and weaknesses of present techniques, paving the way for fog computing research to address unresolved difficulties and anticipate future challenges.
Co-Authors Alfitman Alfitman Alfitman Alfitman Ali, Noraida Haji Atiewi, Saleh Chao, Yu Nur Fazidah Elias Refdinal Nazir Ruzzakiah Jenal Talhouni, Hamed Vera Pujani Yunus, Farizah