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Journal : Science Information System and Technology

Big Data Analysis for Product Demand Prediction in Indonesian E-commerce Afifah Farhanah  Akadji; Rizki Dewantara
West Science Information System and Technology Vol. 2 No. 01 (2024): West Science Information System and Technology
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsist.v2i01.804

Abstract

The Indonesian e-commerce sector has witnessed exponential growth in recent years, necessitating effective strategies for predicting product demand to meet consumer expectations and stay competitive. Leveraging big data analytics offers a promising solution to this challenge, allowing businesses to harness vast volumes of data to forecast demand accurately. This research explores the utilization of big data analysis for product demand prediction in Indonesian e-commerce through a qualitative analysis approach. Interviews with e-commerce executives, data scientists, and industry experts revealed key themes, including data quality and integration, analytical techniques and tools, and organizational culture and capability. Results highlight the challenges, opportunities, and best practices associated with leveraging big data analytics for demand prediction in Indonesian e-commerce, providing valuable insights for businesses striving to optimize their predictive capabilities and enhance decision-making processes in this dynamic and rapidly evolving market.