Prediksi Penjualan Sepatu Dengan Algoritma C4.5 Di T&T Collection Di Tangerang

Abstract

In this modern world, people's need for fashion sports shoes is very important and very much needed for every society. The increasing demand for shoes, store employees have difficulty in recording incoming goods, outgoing goods, and available stock. Employees have difficulty in finding and managing data on incoming goods, outgoing goods, and stock of goods. Inventory data collection still uses paper media, so that there is a buildup of files and there can be a risk of losing the available files. Based on the description of the research background that has been described previously, the objectives of the research are as follows: So that it can be processed more quickly and can accelerate the sales process. By using the C4.5 Algorithm with a decision tree, it can help in collecting data on the available stock of goods. The C4.5 algorithma is used to see sales data patterns in order to generate sales predictions, so that it can provide a decision tree to see sales prediction patterns, so that they can find out how to determine shoe stock inventory patterns based on customer demand needs. With the decision tree method can help in solving problems that occur in the store.Rapid miner will assist in determining which data items are more salable and less salable. The Rapidr miner method will get more accurate decision data and make it easier to analyze goods. Based on the results of the study, the shoes are the most in demand by consumers. Based on the results of research on "Prediction of shoe sales with the C4.5 Algorithm at T&T COllection Stores" with precise accuracy, the authors can conclude that, shoes with old models are less attractive, whereas, new models of shoes with attractive designs sell very well.