Decision Support System for Digital Business Optimization:  A Comparative Analysis of Sales Forecasting Using the Moving Average Method

Dely Indah  Sari; I Made Sondra  Wijaya; Muhammad  Rizki

doi:10.56403/nejesh.v5i1.404

Authors

Dely Indah Sari Institut Teknologi Batam
I Made Sondra Wijaya Institut Teknologi Batam
Muhammad Rizki Institut Teknologi Batam

DOI:

https://doi.org/10.56403/nejesh.v5i1.404

Keywords:

forecasting, moving average, trend semiaverage, weighted moving average

Abstract

This research aims to analyze and compare the accuracy of sales prediction fore-casting methods using three types of Moving Average (MA), namely Simple Moving Average (SMA), Weighted Moving Average (WMA), and Trend Semi Average in the context of digital business optimization. The MA method is used to identify sales trends and assist in planning more effective business strategies. The data used in this research is historical sales data from digital business companies during a certain period. Each MA method is applied to the data to produce sales predictions. The accuracy of each method was evaluated using Mean Absolute Percentage Error (MAPE) as the main metric. This research provides an important contribution for companies in choosing the most appropriate forecasting method to increase operational efficiency and effectiveness. Recommendations resulting from this research can help companies optimize sales strategies and manage inventory better, to increase competitiveness in the market.

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