Items where Author is "Rahman, A.S.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

Baharun, N. and Razi, N.F.M. and Masrom, S. and Yusri, N.A.M. and Rahman, A.S.A. (2022) Auto Modellingfor Machine Learning: A Comparison Implementation between Rapid Miner and Python. International Journal of Emerging Technology and Advanced Engineering, 12 (5). pp. 15-27.

Masrom, S. and Mohd, T. and Rahman, A.S.A. (2022) Green building factor in machine learning based condominium price prediction. IAES International Journal of Artificial Intelligence, 11 (1). pp. 291-299.

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.

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.

Masrom, S. and Rahman, A.S.A. and Omar, N. and Baharun, N. (2019) A new domain specific scripting language for automated machine learning pipeline. International Journal of Recent Technology and Engineering, 8 (2 Spec). pp. 529-534.

Masrom, S. and Abidin, S.Z.Z. and Omar, N. and Rahman, A.S.A. and Rizman, Z.I. (2017) Dynamic parameterizations of particle swarm optimization and genetic algorithm for facility layout problem. ARPN Journal of Engineering and Applied Sciences, 12 (10). pp. 3195-3201.