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All Journal International Journal of Evaluation and Research in Education (IJERE) JOIV : International Journal on Informatics Visualization International Journal of Supply Chain Management
Nur Fazidah Elias
School of IT, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia
Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering Environmental Science Industrial & Manufacturing Engineering Transportation

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Learning management system instrument development based on Aiken’s V technique Ahmad, Nor Azlan; Mayouf, Alanazi Abdulaziz; Elias, Nur Fazidah; Mohamed, Hazura
International Journal of Evaluation and Research in Education (IJERE) Vol 13, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v13i5.28925

Abstract

The use of the learning management system (LMS) at the Malaysian Polytechnic is constantly changing according to the current situation. In addition, the relatively low acceptance of LMS in technical and vocational education training (TVET) institutions requires further study. This paper will discuss accurate construct of measurement for LMS TVET using expert consensus through Aiken's V analysis. Based on the analysis coefficient and the reliability of the content, several important constructs have been identified involving system quality, information quality, service quality, motivation, user satisfaction, intention-to-use, self-discipline, practical training, and actual use. Through quantitative analysis, every item in constructs is calculated and reviewed by an expert in order to validate the items. The minimum validity value accepted in this study is 0.75 based on Aiken's V table, thus, two items were rejected. These items were rejected due to the same meaning and being inappropriate. This study proves the instrument's content validity based on expert agreement using the Aiken agreement index. This study contributes to a suitable instrument for measuring LMS in TVET for use in subsequent studies.
Development of Disruptive Factors for Livestock Supply Chain Abd Majid, Nur Amlya; Sahari@Ashaari, Noraidah; Elias, Nur Fazidah; Mohamed, Hazura
International Journal of Supply Chain Management Vol 8, No 2 (2019): International Journal of Supply Chain Management (IJSCM)
Publisher : ExcelingTech

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59160/ijscm.v8i2.3082

Abstract

This study is conducted to identify disruptive factors affecting the performance of Small Medium Enterprise supply chain in the livestock industry. The role of supply chain management in the livestock industry starts from selection of breeders, equipment suppliers to distribution of slaughter meat to retailers, distributors and end users. Through a preliminary study that was conducted, several disruptive factors in the supply chain of livestock farming have been identified such as natural disasters, distribution of supplies, the behaviour of the stockman and financial. These disruptions have caused losses to stockman, the supply of meat was affected and caused subsequent losses to the country. In relation to that, to identify what are the other factors occurred other than the preliminary study factors, (i) a set of questionnaires based on previous studies was established and validation of the disruptive factors were evaluated by the expert and the survey will be conducted with the respondents. The findings reveal that the factors of husbandry process, financial, stockman, quality of livestock product, farm facilities, technology, demand, supply, information communication, sales, transportation, government involvement, disaster and syariah compliance have been identified as the main disruptive factors in the disruption model. This disruption model will be tested using a statistical technique to identify which factors contribute significantly to the disruption of the supply chain in the livestock farming industry.
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.
Co-Authors Abd Majid, Nur Amlya Ahmad, Nor Azlan Chao, Yu Hazura Mohamed, Hazura Mayouf, Alanazi Abdulaziz Ruzzakiah Jenal Sahari@Ashaari, Noraidah Yazrina Yahya