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Development of a Web-Based Intelligent Market Forecasting System Using Regression Modeling and Data Optimization

Author

Listed:
  • C. O. Ogeh

    (Faculty of Sciences, Department of Computer Science, Delta State University, Abraka, Delta State, Nigeria)

  • G. C. Omede

    (Faculty of Sciences, Department of Computer Science, Delta State University, Abraka, Delta State, Nigeria)

  • F. O. Okorodudu

    (Faculty of Sciences, Department of Computer Science, Delta State University, Abraka, Delta State, Nigeria)

Abstract

Accurate market forecasting is critical for strategic decision-making in the dynamic e-commerce landscape, yet many existing models struggle with scalability and interpretability. This study aims to develop a web-based intelligent forecasting system to provide reliable, real-time market predictions for online retailers. The system employs linear regression, enhanced by robust data preprocessing techniques including cleaning, normalization, and recursive feature elimination (RFE), implemented using HTML, CSS, JavaScript, PHP, SQL, and jQuery. Validation results demonstrate strong performance, with a coefficient of determination (R2) of 0.89 and a 12.5% reduction in Mean Absolute Error (MAE) compared to baseline models. The system’s modular design ensures scalability across retail platforms, while its interpretable outputs support operational planning. This work contributes a practical, lightweight forecasting tool that bridges statistical modeling with modern software engineering, offering online retailers a competitive edge in dynamic digital markets.

Suggested Citation

  • C. O. Ogeh & G. C. Omede & F. O. Okorodudu, 2025. "Development of a Web-Based Intelligent Market Forecasting System Using Regression Modeling and Data Optimization," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 12(6), pages 1015-1025, June.
    • Handle: RePEc:bjc:journl:v:12:y:2025:i:6:p:1015-1025
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