Publications

Year : 2024 | 2023 | 2022 | 2021 | 2020

2024

No	Title	Author(s)
21	Quantum machine learning for corrosion resistance in stainless steel Materials Today Quantum, 2024, 100013 – Elsevier	Muhamad Akrom, Supriadi Rustad, Totok Sutojo, De Rosal Ignatius Moses Setiadi, Hermawan Kresno Dipojono, Ryo Maezono, Moses Solomon
20	A feature restoration for machine learning on anti-corrosion materials Case Studies in Chemical and Environmental Engineering, 10, (2024), 100902 – Elsevier	Supriadi Rustad, Muhamad Akrom, Totok Sutojo, Hermawan Kresno Dipojono
19	Harnessing the XGBoost Ensemble for Intelligent Prediction and Identification of Factors with a High Impact on Air Quality: A Case Study of Urban Areas in Jakarta Province, Indonesia Data Science and Emerging Technologies, 2024, 319–334 – Springer	Wahyu Wibowo, Harun Al Azies, Susi A. Wilujeng & Shuzlina Abdul-Rahman
18	Maximizing complex features to minimize the detectability of content-adaptive steganography Multimedia Tools and Applications, 2024 – Springer	De Rosal Ignatius Moses Setiadi, Supriadi Rustad, Pulung Nurtantio Andono, Guruh Fajar Shidik
17	A comprehensive approach utilizing quantum machine learning in the study of corrosion inhibition on quinoxaline compounds Artificial Intelligence Chemistry, 2 (2), (2024), 100073 – Elsevier	Muhamad Akrom, Supriadi Rustad, Hermawan Kresno Dipojono, Ryo Maezono
16	Machine learning for pyrimidine corrosion inhibitor small dataset Theoretical Chemistry Account, 143, (65), 2024 – Springer	Wise Herowati, Wahyu Aji Eko Prabowo, Muhamad Akrom, Noor Ageng Setiyanto, Achmad Wahid Kurniawan, Novianto Nur Hidayat, Totok Sutojo, Supriadi Rustad
15	Implementation of quantum machine learning in predicting corrosion inhibition efficiency of expired drugs Materials Today Communications, 40, (2024), 109830 – Elsevier	Muhammad Reesa Rosyid, Lubna Mawaddah, Akbar Priyo Santosa, Muhamad Akrom, Supriadi Rustad, Hermawan Kresno Dipojono
14	Variational quantum circuit-based quantum machine learning approach for predicting corrosion inhibition efficiency of pyridine-quinoline compounds Materials Today Quantum, 2, 100007 (2024) – Elsevier	Muhamad Akrom, Supriadi Rustad, Hermawan Kresno Dipojono
13	Development of quantum machine learning to evaluate the corrosion inhibition capability of pyrimidine compounds Materials Today Communications, 39, 108758 (2024) – Elsevier	Muhamad Akrom, Supriadi Rustad, Hermawan Kresno Dipojono
12	SMILES-based machine learning enables the prediction of corrosion inhibition capacity MRS Communications, 14, 379–387, (2024) – Springer	Muhamad Akrom, Supriadi Rustad, Hermawan Kresno Dipojono
11	Prediction of Corrosion Inhibition Efficiency Based on Machine Learning for Pyrimidine Compounds: A Comparative Study of Linear and Non-linear Algorithms KnE Engineering, 68-77, (2024)	Wise Herowati, Wahyu Aji Eko Prabowo, Muhamad Akrom, Totok Sutojo, Noor Ageng Setiyanto, Achmad Wahid Kurniawan, Novianto Nur Hidayat, Supriadi Rustad
10	Implementation of Polynomial Functions to Improve the Accuracy of Machine Learning Models in Predicting the Corrosion Inhibition Efficiency of Pyridine-Quinoline Compounds as Corrosion Inhibitors KnE Engineering, 78-87, (2024)	Setyo Budi, Muhamad Akrom, Harun Al Azies, Usman Sudibyo, Totok Sutojo, Gustina Alfa Trisnapradika, Aprilyani Nur Safitri, Ayu Pertiwi, Supriadi Rustad
9	Prediction of anti-corrosion performance of new triazole derivatives via machine learning Computational and Theoretical Chemistry, 1236, 114599 (2024) – Elsevier	Muhamad Akrom, Supriadi Rustad, Hermawan Kresno Dipojono
8	A machine learning approach to predict the efficiency of corrosion inhibition by natural product-based organic inhibitors Physica Scripta, 99(3), 036006 (2023) – IoP Science	Muhamad Akrom, Supriadi Rustad, Hermawan Kresno Dipojono

2023

No	Title	Author(s)
7	Investigation of Best QSPR-Based Machine Learning Model to Predict Corrosion Inhibition Performance of Pyridine-Quinoline Compounds Journal of Physics: Conf. Ser., 2673(1), 012014 (2023) https://doi.org/10.1088/1742-6596/2673/1/012014	Muhamad Akrom, Totok Sutojo, Ayu Pertiwi, Supriadi Rustad, Hermawan Kresno Dipojono
6	Machine learning investigation to predict corrosion inhibition capacity of new amino acid compounds as corrosion inhibitors Results in Chemistry, 6, 101126 (2023) https://doi.org/10.1016/j.rechem.2023.101126	Muhamad Akrom, Supriadi Rustad, Hermawan Kresno Dipojono
5	Data-driven investigation to model the corrosion inhibition efficiency of Pyrimidine-Pyrazole hybrid corrosion inhibitors Computational and Theoretical Chemistry, 1229, 114307 (2023) https://doi.org/10.1016/j.comptc.2023.114307	Muhamad Akrom, Supriadi Rustad, Adhitya Gandaryus Saputro, Hermawan Kresno Dipojono
4	A combination of machine learning model and density functional theory method to predict corrosion inhibition performance of new diazine derivative compounds Materials Today Communications, 35, 106402 (2023) https://doi.org/10.1016/j.mtcomm.2023.106402	Muhamad Akrom, Supriadi Rustad, Adhitya Gandaryus Saputro, Aditianto Ramelan, Fadjar Fathurrahman, Hermawan Kresno Dipojono
3	A first principle study of adsorption and dissociation of H2 molecule on MoS2 and Ni-promoted MoS2 surfaces AIP Conf. Proc., 2748, 020050 (2023) https://doi.org/10.1063/5.0138531	Wahyu Aji Eko Prabowo, Subagjo Subagjo, Nugraha Nugraha, T Sutojo, Muhamad Akrom, Supriadi Rustad, Hermawan Kresno Dipojono
2	DFT and microkinetic investigation of oxygen reduction reaction on corrosion inhibition mechanism of iron surface by Syzygium Aromaticum extract Applied Surface Science, 615, 156319 (2023), https://doi.org/10.1016/j.apsusc.2022.156319	Muhamad Akrom, Adhitya Gandaryus Saputro, Arifin Luthfi Maulana, Aditianto Ramelan, Ahmad Nuruddin, Supriadi Rustad, Hermawan Kresno Dipojono
1	A machine learning approach for corrosion small datasets npj Materials Degradation, 7(18), (2023) https://doi.org/10.1038/s41529-023-00336-7	Totok Sutojo, Supriadi Rustad, Muhamad Akrom, Abdul Syukur, Guruh Fajar Shidik, Hermawan Kresno Dipojono

2022

2021

2020

English