Implementation Data Mining in Prediction of Sales Chips With Rough Set Method

The introduction of the characteristics of customer transactions can be known from the data in the past to predict future customer needs. In order to be a reference for companies to improve the results of its products. In this study discusses the sales trend of potato chips and bananas in Amira SMEs. Amira SME wants to know the number of sales of potatoes and bananas to agents or resellers and managers by looking at sales trends from the most popular communities so that Amira SMEs can meet customer demand and availability of fixed chips. Data mining can be used to perform data analysis and find important patterns on the data that becomes the benchmark or reference in making decisions. Data mining process can be done by Rough Set method. The Rough Set method offers two forms of data representation namely Information Systems (IS) and Decision Systems (DS). The software that implements Rough Set Algorithm is Rosetta. After analyzing with Rough Set theory, from 7 types of chips and 4 distribution areas to be sampled there are 2 distribution areas (Tebing Tinggi, Medan) and 3 types of chips (real sweet potato, cheese banana, sweet potato roasted corn).