Comparative Analysis Of Exponential Smoothing And Moving Average In Forecasting Popkit RTE Product Demand

Leni Lidya; Mrr. Lukie Trianawati

doi:10.63922/ijebir.v5i04.4800

Leni Lidya Agribusiness Management Study Program, Vocational School, IPB University, Bogor, Indonesia
Mrr. Lukie Trianawati Food Quality Assurance Supervisor Study Program, Vocational School, IPB University, Bogor, Indonesia

DOI: https://doi.org/10.63922/ijebir.v5i04.4800

Keywords: Exponential smoothing, forecasting, manajemen persediaan, moving average, ready-to-eat

Abstract

Popkit is a ready-to-eat (RTE) product consisting of rice topped with chicken and Korean-style sauce, which has become a trending food item popular among university students. The product is marketed through the KlikBi outlet at the Vocational School of IPB University, which serves as the school's entrepreneurship laboratory. The owner of the Popkit business is an alumnus who acts as a business partner of KlikBi. Demand for Popkit is inherently fluctuating due to its sensitivity to the academic calendar, making demand forecasting critical for production efficiency and inventory management. This study aims to compare the accuracy of two forecasting methods Exponential Smoothing (ES, α = 0.3) and 3-Month Moving Average (MAE) and to generate demand predictions for the period of July through December 2026. Monthly sales data from August 2024 to June 2026 (n = 23) were used as the basis for analysis. Forecast accuracy was evaluated using Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). The results indicate that ES outperformed MAE in accuracy (MAE = 567.06; RMSE = 691.96) compared to MAE (MAE = 572.48; RMSE = 737.38). Demand forecasts generated using the ES method for July–December 2026 ranged from 1,069 to 1,103 units per month, with a total projected demand of 6,532 units. These findings can serve as a practical reference for production planning and raw material procurement by the Popkit business management.

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