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

Rahmat Wijaya, Rr. Erlina, Nova Mardiana, Jurusan Manajemen, Universitas Lampung
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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.
移动平均法与指数平滑法在Pd地区香蕉片销售预测中的比较Dwi Putra Tulang bawangbarat
销售预测预测公司的销售情况。过去几年,PD Dwi Putra的香蕉片销量每个月都在波动,导致库存短缺和过剩。使用历史销售数据进行预测使用时间序列方法,如移动平均和指数平滑。本研究比较了两种预测方法,以找到最低的错误率和公司未来四年使用的最佳方法。对于MAPE、MSE和MAD值,指数平滑法优于移动平均法,因此可用于未来预测。据研究,在未来4年,企业应该使用参数为α = 0.6的指数平滑,因为它的预测错误率最低。因此,这些参数被用来预测未来几年。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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