Items where Author is "Rahman, R.A."

Rahman, R.A. and Masrom, S. and Mohamad, M. and Sari, E.N. and Saragih, F. and Rahman, A.S.A. (2023) Comparisons of automated machine learning (AutoML) in predicting whistleblowing of academic dishonesty with demographic and theory of planned behavior. MethodsX, 11. ISSN 22150161

Masrom, S. and Tarmizi, M.A. and Halid, S. and Rahman, R.A. and Abd Rahman, A.S. and Ibrahim, R. (2023) Machine learning in predicting anti-money laundering compliance with protection motivation theory among professional accountants. International Journal of Advanced and Applied Sciences, 10 (7). pp. 48-53.

Ariff, M.I.M. and Khalil, F.M. and Rahman, R.A. and Masrom, S. and Arshad, N.I. (2022) Developing mobile game application for introduction to financial accounting. Indonesian Journal of Electrical Engineering and Computer Science, 27 (3). pp. 1721-1728.

Masrom, S. and Rahman, R.A. and Mohamad, M. and Rahman, A.S.A. and Baharun, N. (2022) Machine learning of tax avoidance detection based on hybrid metaheuristics algorithms. IAES International Journal of Artificial Intelligence, 11 (3). pp. 1153-1163.

Masrom, S. and Rahman, R.A. and Mohamad, M. and Rahman, A.S.A. and Baharun, N. (2022) Machine learning of tax avoidance detection based on hybrid metaheuristics algorithms. IAES International Journal of Artificial Intelligence, 11 (3). pp. 1153-1163.

Masrom, S. and Baharun, N. and Razi, N.F.M. and Rahman, R.A. and Abd Rahman, A.S. (2022) Particle Swarm Optimization in Machine Learning Prediction of Airbnb Hospitality Price Prediction. International Journal of Emerging Technology and Advanced Engineering, 12 (1). pp. 146-151.

Rahman, R.A. and Masrom, S. and Zakaria, N.B. and Nurdin, E. and Abd Rahman, A.S. (2021) Prediction of earnings manipulation on Malaysian listed firms: A comparison between linear and tree-based machine learning. International Journal of Emerging Technology and Advanced Engineering, 11 (8). pp. 111-120.

Rahman, A.S.A. and Masrom, S. and Rahman, R.A. and Ibrahim, R. (2021) Rapid software framework for the implementation of machine learning classification models. International Journal of Emerging Technology and Advanced Engineering, 11 (8). pp. 8-18.