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All Journal Indonesian Geotechnical Journal
Kenandio Darmadi
PT. Haskoning Indonesia
Earth & Planetary Sciences

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Non-Linear Multivariate Analysis with Artificial Neural Network in Estimating Compression Index for Cohesive Soils of Northern Jakarta Coast Andri Mulia; Elyada Eben Ezer; Kenandio Darmadi; M Addifa Yulman; Shandy Yudha Isa; Miftahurrohman; Aditya Hadyan Putra
Indonesian Geotechnical Journal Vol. 3 No. 1 (2024): Vol. 3, No. 1, April 2024
Publisher : Himpunan Ahli Teknik Tanah Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56144/igj.v3i1.80

Abstract

This study presents a novel application of artificial neural network (ANN) to develop a model for predicting compression index (Cc) of cohesive soils from their index properties. The model was trained using data from 347 undisturbed samples on a variety of cohesive soils from Northern Jakarta. It takes up to three variables as inputs: specific gravity (Gs), liquid limit (LL), and plastic limit (PL). The model was tested on a separate dataset of 117 samples and found to have a strong capability to predict Cc values when compared to some reference correlations. The ANN model has demonstrated good performance for each set by producing overall error of 29.6%, compared to 38.1% and 30.5% for the empirical formulas. This study shows that the application of ANN offers an essential advancement in this area, helping to overcome the limitation of conventional statistical correlation.
Co-Authors Aditya Hadyan Putra Andri Mulia Elyada Eben Ezer M Addifa Yulman Miftahurrohman Shandy Yudha Isa