Application of the Weighted Moving Average Method Based on Digital Historical Data for Hijab Sales Prediction

Nur Tiara Annissa; William Ramdhan; Abdul Karim Syahputra

doi:10.30865/jurikom.v12i4.8928

Authors

Nur Tiara Annissa Universitas Royal Asahan Sumatera Utara
William Ramdhan Universitas Royal Asahan Sumatera Utara
Abdul Karim Syahputra Universitas Royal Asahan Sumatera Utara

DOI:

https://doi.org/10.30865/jurikom.v12i4.8928

Keywords:

Business, Syakila Hijab Shop, Forecasting, Weighted Moving Average Method

Abstract

Business can be done by individuals or groups, in the form of small businesses, large companies, or even as individual entrepreneurs. Syakila Hijab Store is one of the businesses engaged in the Muslim fashion sector, especially in providing hijab and Muslim clothing. In the retail industry, the ability to predict sales is very important to optimize stock, reduce the risk of excess or lack of inventory, and increase operational efficiency. Forecasting is making estimates for future testing with past data. The Weighted Moving Average method is generally used to find trends from a time series. This method is used for data that has characteristics that do not change quickly, and do not have seasonal data characteristics. With the existence of a forecasting system that is designed to reduce the problems that occur, it is known that the current problem is the availability of the number of hijab stocks at the Syakila Hijab store which cannot meet consumer demand or excess hijab inventory on certain brands. Inventory pays attention to market demand, to find out market demand a trading business conducts sales forecasting, namely to estimate how much sales might occur in the coming period. A low score indicates a minor error in the prediction.

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