Peramalan Pemesanan Catering Di Kedai Sering Menggunakan Metode Exponential Smoothing Dan Weighted Moving Average
Abstract
This study uses a time series forecasting method, namely applying the Exponential Smoothing and Weighted Moving Average methods to predict the number of Catering orders in the following month at the SERING shop. The data used in this study were obtained from historical records of orders for 29 months and grouped into three service categories: Package 1, Package 2, and Package 3. The forecasting process is carried out by applying various parameter values, namely α = 0.1, 0.5, and 0.9 for the Exponential Smoothing method, and weights of 1, 2, and 3 for the Weighted Moving Average method with 3 data periods. To evaluate the accuracy of each method, three error measures are used: Mean Absolute Deviation (MAD), Mean Squared Error (MSE), and Mean Absolute Percentage Error (MAPE). The results of the analysis show that the Exponential Smoothing method with α = 0.9 consistently produces the smallest error value compared to other methods. Thus, this method is considered the most optimal and can be used as a basis for planning raw material procurement and making operational decisions in the future.
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