Dr Satrya Fajri Pratama BCS (Hons), MSc, P.Tech.(ICT)
Lecturer
Summary
About
Teaching
School of Computing and Digital Technologies
College of Business, Technology and Engineering
Publications
Journal articles
Mohd Yusof, N., Muda, A.K., Pratama, S.F., & Abraham, A. (2023). A novel nonlinear time-varying sigmoid transfer function in binary whale optimization algorithm for descriptors selection in drug classification. Molecular diversity, 27 (1), 71-80. http://doi.org/10.1007/s11030-022-10410-y
Zulfikar, W.B., Atmadja, A.R., & Pratama, S.F. (2023). Sentiment analysis on social media against public policy using multinomial naive bayes. Scientific Journal of Informatics, 10 (1), 25-34. http://doi.org/10.15294/sji.v10i1.39952
Pratiwi, L., Choo, Y.H., Muda, A.K., & Pratama, S.F. (2023). Covariance Search Model for Identifying ncRNA using Particle Swarm Optimized Agglomerative Clustering. International Journal of Computer Information Systems and Industrial Management Applications, 15 (2023), 460-468.
Pratiwi, L., Choo, Y.-.H., Muda, A.K., & Pratama, S.F. (2022). Swarm Intelligence-based Hierarchical Clustering for Identification of ncRNA using Covariance Search Model. International Journal of Advanced Computer Science and Applications (IJACSA), 13 (11), 822-831. http://doi.org/10.14569/IJACSA.2022.0131195
Mohd Yusof, N., Muda, A.K., Pratama, S.F., Carbo-Dorca, R., & Abraham, A. (2022). Improving Amphetamine-type Stimulants drug classification using chaotic-based time-varying binary whale optimization algorithm. Chemometrics and Intelligent Laboratory Systems, 229, 104635. http://doi.org/10.1016/j.chemolab.2022.104635
Mohd Yusof, N., Muda, A.K., Pratama, S.F., Carbo-Dorca, R., & Abraham, A. (2022). Improved swarm intelligence algorithms with time-varying modified Sigmoid transfer function for Amphetamine-type stimulants drug classification. Chemometrics and Intelligent Laboratory Systems, 226, 104574. http://doi.org/10.1016/j.chemolab.2022.104574
Mohd Yusof, N., Muda, A.K., Pratama, S.F., & Carbo-Dorca, R. (2022). Amphetamine-type stimulants (ATS) drug classification using shallow one-dimensional convolutional neural network. Molecular diversity, 26 (3), 1609-1619. http://doi.org/10.1007/s11030-021-10289-1
Yusof, N.M., Muda, A.K., & Pratama, S.F. (2021). Swarm Intelligence-Based Feature Selection for Amphetamine-Type Stimulants (ATS) Drug 3D Molecular Structure Classification. Applied Artificial Intelligence, 35 (12), 914-932. http://doi.org/10.1080/08839514.2021.1966882
Pratama, S.F., Muda, A.K., Choo, Y.H., Carbó-Dorca, R., & Abraham, A. (2018). Preparation of translated, scaled, and rotated ATS Drugs 3D molecular structure for the validation of 3D moment invariants-based molecular descriptors. International Journal of Computer Information Systems and Industrial Management Applications, 10, 057-067.
Pratama, S.F., Muda, A.K., & Choo, Y.H. (2018). Arbitrarily substantial number representation for complex number. Journal of Telecommunication, Electronic and Computer Engineering, 10 (1-7), 23-26.
Pratama, S.F., Muda, A.K., Choo, Y.-.H., Flusser, J., & Abraham, A. (2017). ATS drugs molecular structure representation using refined 3D geometric moment invariants. Journal of Mathematical Chemistry, 55 (10), 1951-1963. http://doi.org/10.1007/s10910-017-0775-3
Bero, S.A., Muda, A.K., Choo, Y.H., Muda, N.A., & Pratama, S.F. (2017). Similarity Measure for Molecular Structure: A Brief Review. Journal of Physics: Conference Series, 892, 012015. http://doi.org/10.1088/1742-6596/892/1/012015
Pratama, S.F., Muda, N.A., & Salim, F. (2017). Representing ATS drugs molecular structure using 3D orthogonal Fourier-Mellin moments. International Journal of Computer Information Systems and Industrial Management Applications, 9, 135-144.
Pratama, S.F., Muda, A.K., Choo, Y.-.H., & Muda, N.A. (2013). SOCIFS feature selection framework for handwritten authorship. International Journal of Hybrid Intelligent Systems, 10 (2), 83-91. http://doi.org/10.3233/his-130167
Conference papers
Yusof, N.M., Muda, A.K., Pratama, S.F., Carbo-Dorca, R., & Abraham, A. (2023). Binary whale optimization algorithm with logarithmic decreasing time-varying modified sigmoid transfer function for descriptor selection problem. Proceedings of the 14th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2022), 673-681. http://doi.org/10.1007/978-3-031-27524-1_65
Mohd Yusof, N., Muda, A.K., Pratama, S.F., & Abraham, A. (2022). Improving Amphetamine-Type Stimulants Drug Classification Using Binary Whale Optimization Algorithm as Relevant Descriptors Selection Technique. In Lecture Notes in Networks and Systems, (pp. 424-432). Springer International Publishing: http://doi.org/10.1007/978-3-030-96302-6_39
Knight, P.E., Muda, A.K., & Pratama, S.F. (2022). Analysis of Feature Selection Method for 3D Molecular Structure of Amphetamine-Type Stimulants (ATS) Drugs. In Lecture Notes in Networks and Systems, (pp. 118-135). Springer International Publishing: http://doi.org/10.1007/978-3-030-96302-6_11
Pratama, S.F., Muda, A.K., Choo, Y.-.H., Carbó-Dorca, R., & Abraham, A. (2021). Using 3D Hahn Moments as A Computational Representation of ATS Drugs Molecular Structure. In Advances in Intelligent Systems and Computing, (pp. 90-101). Springer International Publishing: http://doi.org/10.1007/978-3-030-49345-5_10
Pratama, S.F., Muda, A.K., Choo, Y.-.H., & Abraham, A. (2018). Preparation of ATS Drugs 3D Molecular Structure for 3D Moment Invariants-Based Molecular Descriptors. In Advances in Intelligent Systems and Computing, (pp. 252-261). Springer International Publishing: http://doi.org/10.1007/978-3-319-76351-4_26
Bero, S.A., Muda, A.K., Choo, Y.-.H., Muda, N.A., & Pratama, S.F. (2014). Rotation analysis of moment invariant for 2D and 3D shape representation for molecular structure of ATS drugs. 2014 4th World Congress on Information and Communication Technologies (WICT 2014), 308-313. http://doi.org/10.1109/wict.2014.7077285
Pratama, S.F., Muda, A.K., Abraham, A., & Muda, N.A. (2013). An Alternative to SOCIFS Writer Identification Framework for Handwritten Authorship. 2013 IEEE International Conference on Systems, Man, and Cybernetics, 1007-1012. http://doi.org/10.1109/smc.2013.176
Pratama, S.F., Muda, A.K., Choo, Y.-.H., & Muda, N.A. (2011). PSO and Computationally Inexpensive Sequential Forward Floating Selection in acquiring significant features for handwritten authorship. 2011 11th International Conference on Hybrid Intelligent Systems (HIS), 358-363. http://doi.org/10.1109/his.2011.6122132
Book chapters
Pratama, S.F., Muda, A.K., Choo, Y.-.H., & Abraham, A. (2017). 3D Geometric Moment Invariants for ATS Drugs Identification: A More Precise Approximation. In Advances in Intelligent Systems and Computing. (pp. 124-133). Springer International Publishing: http://doi.org/10.1007/978-3-319-52941-7_13
Pratama, S.F., Muda, A.K., Choo, Y.-.H., & Abraham, A. (2016). Exact Computation of 3D Geometric Moment Invariants for ATS Drugs Identification. In Advances in Intelligent Systems and Computing. (pp. 347-358). Springer International Publishing: http://doi.org/10.1007/978-3-319-28031-8_30
Pratama, S.F., Muda, A.K., Choo, Y.-.H., & Abraham, A. (2015). A Comparative Study of 2D UMI and 3D Zernike Shape Descriptor for ATS Drugs Identification. In Advances in Intelligent Systems and Computing. (pp. 237-249). Springer International Publishing: http://doi.org/10.1007/978-3-319-17398-6_22
Pratama, S.F., Pratiwi, L., Abraham, A., & Muda, A.K. (2014). Computational Intelligence in Digital Forensics. In Studies in Computational Intelligence. (pp. 1-16). Springer International Publishing: http://doi.org/10.1007/978-3-319-05885-6_1
Pratama, S.F., Muda, A.K., Choo, Y.-.H., & Muda, N.A. (2014). A New Swarm-Based Framework for Handwritten Authorship Identification in Forensic Document Analysis. In Studies in Computational Intelligence. (pp. 385-411). Springer International Publishing: http://doi.org/10.1007/978-3-319-05885-6_16
Muda, A.K., Pratama, S.F., Choo, Y.-.H., & Muda, N.A. (2011). Selecting Significant Features for Authorship Invarianceness in Writer Identification. In Communications in Computer and Information Science. (pp. 637-651). Springer Berlin Heidelberg: http://doi.org/10.1007/978-3-642-22170-5_55