A
Amirrudin Kamsin
Researcher at Information Technology University
Publications - 86
Citations - 1982
Amirrudin Kamsin is an academic researcher from Information Technology University. The author has contributed to research in topics: Computer science & Big data. The author has an hindex of 18, co-authored 79 publications receiving 1153 citations. Previous affiliations of Amirrudin Kamsin include University of Kuala Lumpur & University College London.
Papers
More filters
Journal ArticleDOI
Challenges in the online component of blended learning: A systematic review
TL;DR: A systematic review of literature was conducted with the aim of identifying the challenges in the online component of blended learning from students, teachers and educational institutions perspectives.
Journal ArticleDOI
Malicious accounts
TL;DR: A comprehensive review of related studies that deal with detection of malicious accounts on social networking sites focusing on four main categories, which include detection of spam accounts, fake accounts, compromised accounts, and phishing.
Journal ArticleDOI
Computational intelligence approaches for classification of medical data: State-of-the-art, future challenges and research directions
Ali Kalantari,Amirrudin Kamsin,Shahaboddin Shamshirband,Abdullah Gani,Hamid Alinejad-Rokny,Anthony T. Chronopoulos,Anthony T. Chronopoulos +6 more
TL;DR: The results show that Support Vector Machine and Artificial Immune Recognition System as a single based computational intelligence approach were the best methods in medical applications and the hybridization of SVM with other methods had great performances achieving better results in terms of accuracy, sensitivity and specificity.
Journal ArticleDOI
A bibliometric approach to tracking big data research trends
Ali Kalantari,Amirrudin Kamsin,Halim Shukri Kamaruddin,Nader Ale Ebrahim,Abdullah Gani,Ali Ebrahimi,Shahaboddin Shamshirband +6 more
TL;DR: The novelty of this study is that it provides a formula from multi-regression analysis for citation analysis based on the number of authors, number of pages and number of references to prove the hypothesis statistically and characterize the relationship among the variables.
Journal ArticleDOI
Comparative analysis of reference evapotranspiration equations modelling by extreme learning machine
TL;DR: Results showed that ELM ET0,AHARG can be applied to forecast ET0 effectively and was found to be superior in modelling monthly ET0 than the other models, respectively.