CD Skripsi
Korelasi Empiris Prediksi Nilai Cbr Berdasarkan Nilai Cone Resistance Melalui Simulasi Campuran Pasir Dan Lempung Bentonit – Kaolin
ABSTRACT
In geotechnical engineering, professional actions and expert judgment are often
essential in soil investigation methods. In coastal areas, expansive soils with sandy
sedimentation lead to reduced bearing capacity and challenges in field
instrumentation. This study models a clayey sand (SC) mixture using Bentonite and
Kaolin as fine fractions, which exhibit expansive behavior and poor gradation. The
mechanical behavior of the soil is evaluated through modified compaction tests,
using California Bearing Ratio (CBR, %) and Cone Resistance (Qc, kg/cm²) as
bearing capacity parameters. Soil mixtures were simulated with sand fractions ≥
65% and Bentonite-Kaolin compositions with ≥ 50% Bentonite. Compaction was
modeled using variations in compaction energy and water content, under
conditions below the maximum dry density (γdrymax). CBR prediction was conducted
using Qc as the primary predictor, and dry density (γdry) as a supporting predictor
that directly influences bearing capacity. A hybrid stepwise regression analysis in
Z-score scale identified positively correlated predictors: +3.0296 (Qc), +0.5588
(γdry), and +1.2766 (Qc * γdry interaction). The regression model shows strong
statistical performance with R² = 0,84, and high significance with P-values of
2×10⁻¹⁵ (Qc), 4×10⁻² (γdry), and 3×10⁻⁶ (Qc * γdry interaction). The resulting
regression equation offers an applicable approach to evaluate the bearing capacity
of subgrade soils in coastal conditions, thereby facilitating geotechnical
engineering design and optimization processes in the field.
Keywords : coastal subgrade, prediction of CBR, bearing capacity, stepwise
regression
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