Optimization of Sugarcane Bagasse Ash Waste Utilization as Advanced Material in Normal Concrete Using Artificial Intelligence

DOI

10.2991/978-94-6463-920-9_29How to use a DOI?

Keywords

Normal Concrete; Sugarcane Bagasse Ash Waste; Pozzolan; Artificial Intelligence

Abstract

PT Gula Glenmore produces 270,000 tons of sugarcane bagasse per milling season, mostly unused and environmentally harmful. This study aims to utilize sugarcane bagasse ash as an alternative pozzolanic material for concrete, replacing cement with the aid of artificial intelligence (machine learning). The methods used include linear regression, decision tree, and random forest to predict the performance of normal concrete mixtures with a compressive strength of 30 MPa, shaped into cylinders (30 cm of height and, 15 cm of diameter).Prediction results indicate that the random forest method identifies the optimal composition of bagasse ash with a compressive strength of 25.33 MPa from 1.33% bagasse ash, which is more accurate compared to the linear regression method (24.37 MPa with 1.18%) and the decision tree method (25.03 MPa with 0.73%). Laboratory tests show compressive strengths of X12: 25 MPa, X22: 24 MPa, and X23: 26 MPa, respectively. The random forest method provides more accurate predictions due to its ability to capture non-linear relationships, although it requires higher computational resources and results in more complex interpretations. This research is expected to reduce trial and error in further research on the use of sugarcane bagasse ash as a pozzolanic material.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Nanin Utami
AU  - Widya Cahyadi
AU  - Ketut Wiswamitra
AU  - Shafiril Ramdani
AU  - Diofani Mochammad
PY  - 2025
DA  - 2025/12/15
TI  - Optimization of Sugarcane Bagasse Ash Waste Utilization as Advanced Material in Normal Concrete Using Artificial Intelligence
BT  - Proceedings of the International Conference on Recent Innovations in Sustainable Engineering Solutions 2025 (ICONRISES 2025)
PB  - Atlantis Press
SP  - 300
EP  - 309
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-920-9_29
DO  - 10.2991/978-94-6463-920-9_29
ID  - Utami2025
ER  -