Analyzing the Pandemic Effect on Time series Prediction of Demand and Sales Manufacturing Product

Abstract

The purpose of this study is to predict the demand and sales of plastic products in 2021 accompanied by the Covid 19 pandemic. This research is a quantitative descriptive study using time series forecasting methods and data analysis using Microsoft Excel. The data used as research is sales and monthly demand data for the years 2018-2020, totaling thirty-six data. Data collection was done by using documentation method. Analysis of the 2018-2020 data shows fluctuating demand and sales data. The 2018-2020 sales data research revealed fluctuations in demand and sales, influenced by the general annual season and the impact of the Covid 19 pandemic. Analysis of the demand forecast for 2021 gives the highest demand results in December and the lowest demand in June. Forecasting sales, the highest result in October, and the lowest sales in June. This means that fluctuations in demand and sales are affected by seasonality and government regulations. Based on this analysis, it can be concluded that forecasting using the time series forecasting method gives inaccurate results because there are many unexpected events, one of which is the Covid-19 pandemic which causes the local government to issue new regulations for sellers of examples of changes in selling prices. Therefore, the company must prepare the right strategy to deal with events that do not match expectations. Keywords—demand forecasting, sales forecasting, time series forecasting