Sales Prediction Based on Sales Data Analysis Using the Moving Average Algorithm (Case in hawada refill drinking water)

Abstract

Hawada refill drinking water depot is a line of business providing hygienic refill drinking water, which is packaged in gallon packaging which in its transaction activities still uses the SMS feature. The problem faced by the Hawada refill drinking water depot is that there is no distributed application that can assist transaction management activities, so that data input and transaction data are still manually calculated for report generation. Previous sales data has not been processed into useful information. The solution to this problem is to predict sales of refill drinking water based on sales data analysis using a moving average algorithm. By designing applications that can manage consumer transaction activities, so that data input and sales data calculations can be done automatically for report generation. As well as analyzing previous sales data, so as to get useful information to predict sales for the next period. The method is to create a mobile application to monitor online transaction activities using Hybrid Programming Technology based on the Ionic Framework, with analysis of previous sales data which will be processed by the Moving Average Algorithm to predict sales data for the next period. The designed application can process transaction activities and process previous sales data using a moving average algorithm, producing accurate predictive data in the form of sales graph reports.