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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Indonesian Journal of Electrical Engineering and Computer Science
Lizawati Mi Yusuf
Universiti Teknologi Malaysia
Computer Science & IT

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Analysis and Identification the Complexity of Data Heterogeneity on Learning Environment Using Ontology Arda Yunianta; Mohd Shahizan Othman; Norazah Yusof; Lizawati Mi Yusuf; Juwairiah Juwairiah; Nurul Syazana Selamat
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 13, No 1: March 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v13i1.1321

Abstract

Distributed and various systems on learning environment are the current issues to produce big data and heterogeneity data problem. Heterogeneity on learning environment is about numerous learning applications and various learning information to support a learning process in educational institutions. There are a lot of relationships are formed between elements on learning environment. The elements on learning environment consist of learning data, learning applications, data sources, learning concept, and data heterogeneity aspect on learning environment. These elements are interrelated and produce complex relationship between each other. A complex relationship problem between elements on learning environment makes a process of analysis and identification difficult to be done. Existing method to drawing this heterogeneity problem make confuse and misunderstanding readers. To solved this problem, researcher using ontology knowledge to describe and draw a semantic relationship that represent the complexity of data relationship on learning environment. The result of this analysis is to develop ontology knowledge to solve heterogeneity data problem specific in complexity relationship on learning environment. This result can give better understanding to the readers about complex relationship between elements on learning environment.
A model of acceptance factors for business intelligence in manufacturing using theoretical models Ernie Mazuin Mohd Yusof; Mohd Shahizan Othman; Lizawati Mi Yusuf; Shamini Raja Kumaran; Ahmad Rizal Mohd Yusof
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 3: June 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v14.i3.pp1544-1551

Abstract

Manufacturing organizations implemented Business Intelligence (BI) due to many advantages offered by it. The lack of research on the acceptance of BI in manufacturing motivates the initiative in this study to have an understanding of the factors that influence the acceptance of BI in manufacturing sector. Therefore, the research proposes a model which indicates the acceptance factors of BI in manufacturing. An integrated model consisting of underlying models of Technology Acceptance Model (TAM), Expectation Confirmation Theory (ECT) and Task-Technology Fit (TTF) will be developed. The new model will formulate 19 hypotheses and 11 factors contributing to the continuance and acceptance of BI. The model will be tested using quantitative and qualitative survey conducted to Malaysian manufacturing companies and validated using Structural Equation Modelling (SEM) to investigate the causal and mediating relationships between the factors. The expected result is hoping to suggest that selected factors in the model are positively related towards the acceptance of BI in manufacturing. The results are also hoping to guide future initiatives by industrial practitioners to develop and distribute BI to the manufacturing market.
Co-Authors Ahmad Rizal Mohd Yusof Arda Yunianta Ernie Mazuin Mohd Yusof Juwairiah Juwairiah Mohd Shahizan Othman Norazah Yusof Nurul Syazana Selamat Shamini Raja Kumaran