Application of the Naïve Bayes Algorithm in Predicting Sales Prices for Snacks - Gulo, Maleakhi; Sumarno, Sumarno; Anggraini, Fitri (Yayasan Literasi Sains Indonesia, 2023)
This study aims to apply the Naïve Bayes Algorithm in predicting the selling price of snacks at Toko Timbul II. The data used in this study were obtained from January to December 2018-2021, covering various variables relevant to snack sales. The data collected is divided into two parts, namely Data Training and Data Testing. The Training Data consists of 20 alternatives, which are used to train the prediction model of the Naïve Bayes Algorithm. While Data Testing consists of 16 alternatives, which are used to test the extent of the model's ability to predict the selling price of snacks. Testing was carried out using the Rapid Miner application. The test results show that the implemented model achieves an accuracy rate of 100% in predicting the selling price of snacks. These results indicate that the Naïve Bayes Algorithm has great potential in predicting the selling price of snacks at Timbul II Stores. These findings can provide valuable insights for store managers and snack food industry stakeholders, as well as encourage the use of predictive analytical methods in similar contexts. It is hoped that the results of this study can contribute to optimizing sales strategies and making more informed decisions in the future.