T
Tutut Herawan
Researcher at University of Malaya
Publications - 326
Citations - 5757
Tutut Herawan is an academic researcher from University of Malaya. The author has contributed to research in topics: Soft set & Rough set. The author has an hindex of 34, co-authored 318 publications receiving 4860 citations. Previous affiliations of Tutut Herawan include Multimedia University & Universiti Tun Hussein Onn Malaysia.
Papers
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Journal ArticleDOI
A Systematic Review on Educational Data Mining
TL;DR: This paper provides over three decades long systematic literature review on clustering algorithm and its applicability and usability in the context of EDM.
Journal ArticleDOI
Information security conscious care behaviour formation in organizations
Nader Sohrabi Safa,Mehdi Sookhak,Rossouw von Solms,Steven Furnell,Norjihan Abdul Ghani,Tutut Herawan +5 more
TL;DR: The results of structural equation modelling (SEM) showed that Information Security Awareness, Information Security Organization Policy, information Security Experience and Involvement, Attitude towards information security, Subjective Norms, Threat Appraisal, and Information Security Self-efficacy have a positive effect on users' behaviour, however, Perceived Behavioural Control does not affect their behaviour significantly.
Journal ArticleDOI
The Relationship between Study Anxiety and Academic Performance among Engineering Students
Prima Vitasari,Muhammad Nubli Abdul Wahab,Ahmad Othman,Tutut Herawan,Suriya Kumar Sinnadurai +4 more
TL;DR: In this article, the authors observed the relationship between study anxiety level and students' academic performance and found that there was a significant correlation of high level anxiety and low academic performance among engineering students, with significant correlation (p = 0.000) and the correlation coefficient is small with r ǫ −264.
Journal ArticleDOI
A soft set approach for association rules mining
Tutut Herawan,Mustafa Mat Deris +1 more
TL;DR: This paper defines the notion of regular and maximal association rules between two sets of parameters, also their support, confidence and maximal support, maximal confidences, respectively properly using soft set theory, and shows that the soft regular and soft maximal associationrules provide identical rules as compared to the regular and minimal association rules.
Book ChapterDOI
Big Data Clustering: A Review
TL;DR: The trend and progress of clustering algorithms to cope with big data challenges from very first proposed algorithms until today's novel solutions are reviewed and the possible future path for more advanced algorithms is illuminated based on today’s available technologies and frameworks.