Forecasting Rice Sales Using Weighted Moving Average Method: Case Study at KAKANG MART GROSIR Bandung

https://doi.org/10.47194/ijgor.v6i3.395

Authors

  • Nenden Siti Nurkholipah
  • Tubagus Robbi Megantara Department of Mathematics, Faculty of Mathematics and Natural Sciences, The National University of the Republic of Indonesia, Bandung, Indonesia
  • Rizki Apriva Hidayana Department of Mathematics, Faculty of Mathematics and Natural Sciences, The National University of the Republic of Indonesia, Bandung, Indonesia

Abstract

Effective inventory management is critical for retail businesses, and accurate sales forecasting is its cornerstone, especially for staple products like rice. This study aims to forecast the sales of packaged rice at KAKANG MART GROSIR, a major retailer in Bandung, by analyzing its daily sales data. The research utilizes the Weighted Moving Average (WMA) method on primary sales data for six top-selling rice brands collected over a three-month period from March 1 to May 31, 2025. The WMA model, which assigns greater importance to recent observations, was employed to smooth short-term fluctuations and identify underlying sales trends. The analysis revealed highly dynamic and distinct sales patterns: the JM Cianjur brand showed the highest average sales but with significant weekly volatility , the Setrawangi RS brand demonstrated strong and consistent growth to become a market leader , while the Setrawangi DI brand experienced a sharp decline. Furthermore, the BMW brand was found to have remarkably stable and predictable sales , whereas the Lahap and Sedap Wangi brands consistently remained at the lowest sales tier. The findings confirm that the WMA is a valuable tool for identifying diverse sales trajectories, providing actionable insights for developing tailored inventory strategies for each product.

Published

2025-08-25