Background: Microplastic pollution in coastal waters poses a serious threat to marine ecosystem sustainability and human health due to its persistence and widespread distribution. Since microplastics degrade very slowly under natural conditions, innovative and environmentally friendly mitigation strategies are urgently required. This study introduces BLUEPOD (Buoyant Layered Underwater Ecofilter Pod), an active biosorbent system designed as a floating module composed of a multilayer fibrous matrix integrated with laccase enzyme derived from Aspergillus oryzae and activated carbon. Methods: The activated carbon functions as a high-surface-area adsorbent for capturing microplastic particles, while the immobilized laccase promotes oxidative modification of polymer surfaces, enhancing degradation and reducing persistence. The performance of BLUEPOD was evaluated under controlled laboratory-scale experimental conditions, including static batch tests and continuous-flow tank experiments, using defined concentrations of synthetic microplastics (<5 mm). Removal efficiency was assessed over a 48-hour operational period. Findings: The results demonstrated that BLUEPOD achieved more than 80% microplastic removal efficiency, indicating a strong synergistic effect between adsorption and enzymatic oxidation mechanisms. These findings highlight the potential of BLUEPOD as a lab-scale validated biosorbent system with promising applicability for coastal water treatment, riverine environments, and aquaculture discharge management. Conclusion: With further optimization and field-scale validation, BLUEPOD may serve as a sustainable and scalable solution for mitigating microplastic pollution in Indonesia’s coastal regions and other similarly impacted marine environments. Novelty/Originality of this article: The novelty of this study lies in developing BLUEPOD, a floating multilayer fiber biosorbent integrating Aspergillus oryzae laccase and activated carbon, combining adsorption and enzymatic oxidation for effective microplastic removal.