Implementation of data mining to estimate the need for toast bread supply at junction cafe using the multiple linear regression method

Abstract

Junction Cafe Medan, which is managed by individuals, has a large supply of bread services with different specifications. The inventory system for toasted bread at Junction Cafe Medan still uses a manual system in data processing. Handling data with this system has several obstacles, including causing shortages and excesses of bread stock, impacting guests due to running out of bread stock, excessive costs incurred for stocking bread, and lack of accuracy in recording incoming and outgoing bread stock resulting in shortages and errors in ending stock inventory. Based on this research problem, a data mining application is needed that is capable of estimating bread supplies at Junction Café Medan, where each Bread inventory data at Junction Café Medan will be calculated using one of the data mining methods that is capable of estimating bread supplies based on bread usage by applying the Regression method Multiple Linear The result of this research is a data mining application that uses the Multiple Linear Regression method which is able to solve the bread stock inventory problem at Junction Cafe Medan by estimating bread stock inventory more quickly and accurately