Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal International Journal of Acta Material
Hikmayani
Department of Chemistry. Faculty of Mathematics and Natural Sciences. Halu Oleo University. Kendari. Indonesia.
Chemistry Materials Science & Nanotechnology Physics

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Optimisation of Asphalt Extraction from Asbuton Using Microwave-Assisted Extraction (MAE) Method Hikmayani; I W. Sutapa; Sahidin; L. O. Ahmad
International Journal of Acta Material Vol. 2 No. 1 (2025): August 2025
Publisher : Faculty Mathematics and Natural Sciences, Halu Oleo University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62749/ijactmat.v2i1.19

Abstract

Buton natural asphalt (Asbuton) is a strategic non petroleum bitumen resource with promising potential in road construction. However, conventional extraction methods such as Soxhlet and reflux suffer from long processing times, high energy demand, and excessive solvent use. This review evaluates Microwave-Assisted Extraction (MAE) as a green and efficient alternative for extracting bitumen from Asbuton. MAE employs rapid dielectric heating, enabling selective bitumen release while minimizing solvent consumption. Key process variables, including solvent polarity, solid-to-solvent ratio, temperature, extraction time, microwave power, and system pressure are critically reviewed. Comparative data show that MAE significantly improves extraction yield and operational efficiency. In addition, Response Surface Methodology (RSM) is discussed as a modeling tool to optimize variable interactions and identify ideal extraction conditions. Visual aids such as flow diagrams and comparative tables are used to clarify performance metrics and technical constraints. The review also outlines major challenges in MAE implementation, including microwave penetration in low-dielectric matrices and the need for scalable reactor designs. Overall, this paper provides a comprehensive perspective on MAE-based extraction for Asbuton, offering insight into its advantages, limitations, and directions for future research and industrial application.
Adoption of Computational Response Surface Methodology (RSM) in Asphalt Research I W. Sutapa; Hikmayani; G. R. Lempang; L. O. Kadidae; I N. Sudiana; A. Bandjar
International Journal of Acta Material Vol. 2 No. 2 (2026): February 2026
Publisher : Faculty Mathematics and Natural Sciences, Halu Oleo University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62749/ijactmat.v2i2.34

Abstract

Response Surface Methodology (RSM) is a powerful statistical and computational tool used to model and optimize complex systems involving multiple variables and responses. In asphalt research, RSM has gained significant attention for its efficiency in optimizing mix design, evaluating modified asphalt properties, and analyzing the effects of processing and environmental conditions. This review highlights the application of RSM in key aspects of asphalt studies, including experimental design (CCD, BBD, factorial), mathematical modeling, response visualization, and multi-response optimization. The use of RSM enables researchers to identify optimal binder content, additive dosage, and process conditions with reduced experimental effort. Additionally, the integration of RSM with contour and 3D surface plots provides intuitive understanding of parameter interactions. Despite its advantages, RSM faces limitations such as model assumptions, sensitivity to data distribution, and challenges in field validation. Future research is encouraged to combine RSM with artificial intelligence techniques for more robust predictions and to validate laboratory models under real-world conditions. Overall, RSM remains a valuable methodology for advancing asphalt technology, especially in the development of sustainable and high-performance pavement materials.  
Co-Authors A. Bandjar G. R. Lempang I N. Sudiana I W. Sutapa I W. Sutapa L. O. Ahmad L. O. Kadidae Sahidin