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

C. O. Ogeh, G. C. Omede and F. O. Okorodudu
Additional contact information
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

International Journal of Research and Scientific Innovation, 2025, vol. 12, issue 6, 1015-1025

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.

Date: 2025
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.rsisinternational.org/journals/ijrsi/d ... ssue-6/1015-1025.pdf (application/pdf)
https://rsisinternational.org/journals/ijrsi/artic ... d-data-optimization/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bjc:journl:v:12:y:2025:i:6:p:1015-1025

Access Statistics for this article

International Journal of Research and Scientific Innovation is currently edited by Dr. Renu Malsaria

More articles in International Journal of Research and Scientific Innovation from International Journal of Research and Scientific Innovation (IJRSI)
Bibliographic data for series maintained by Dr. Renu Malsaria ().