Comparison of Moving Average and Exponential Smoothing Methods in Sales Forecasting of Banana Chips Products in Pd. Dwi Putra Tulang Bawang Barat

Rahmat Adi Wijaya; Rr. Erlina; Nova Mardiana

doi:10.55927/jfbd.v2i2.4913

Authors

Rahmat Adi Wijaya Jurusan Manajemen, Universitas Lampung
Rr. Erlina Jurusan Manajemen, Universitas Lampung
Nova Mardiana Jurusan Manajemen, Universitas Lampung

DOI:

https://doi.org/10.55927/jfbd.v2i2.4913

Keywords:

Sales Forecasting, Moving Average, Exponential Smoothing

Abstract

Sales forecasts predict a company's sales. PD Dwi Putra's banana chip sales have fluctuated every month for the past few years, resulting in stock shortages and excesses. Forecasting using historical sales data uses time series methods like moving average and exponential smoothing. This study compares the two forecasting methods to find the lowest error rate and the best method for the company to use for the next four years. The exponential smoothing method outperforms the moving average method for MAPE, MSE, and MAD values, so it is used for future forecasting. According to research, companies should use exponential smoothing with parameter α = 0.6 for the next four years because it has the lowest forecasting error rate. Thus, these parameters are used to forecast the next few years.

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