The increasing demand for environmentally friendly materials has intensified research on natural fiber composites. Bamboo fiber is a promising reinforcement material because of its high tensile strength, low density, and abundant availability. However, optimizing processing parameters and developing reliable predictive models for bamboo fiber tensile strength remain challenging. Therefore, this study aims to identify optimal processing parameters and develop a continuous predictive model for bamboo fiber tensile strength. A full-factorial design of experiments was employed using four variables: bamboo type, NaOH concentration, immersion time, and immersion temperature. Experimental data were analyzed using the Signal-to-Noise ratio, Analysis of Variance, and General Linear Model to evaluate factor significance and contribution. The results showed that bamboo type and immersion time were the most influential factors affecting tensile strength. The optimum configuration was obtained using rope bamboo treated with 4% NaOH for 2 h at 25 °C. A continuous predictive equation was developed using least-squares regression and showed a statistically significant moderate-to-strong correlation with the experimental run means (r = 0.715, p 0.01). The proposed equation is applicable for interpolation within the tested parameter ranges. The study provides a full-factorial predictive framework for bamboo fiber processing, although independent validation is required before broader application.
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