Penerapan Data Mining Menggunakan Metode Algoritma Naive Bayes Classifier untuk Mendukung Strategi Promosi

Aulia Yahyah Sari (Universitas Ma’soem)
Encep Supriatna (Universitas Ma’soem)

Jurnal Dimamu
Vol. 3 No. 1 (2023)

The purpose of this study is to make it easier to find out the prediction results with the classification method from PPDB data for 2021-2022 to support promotion strategies at the Skye Foundation with the Naive Bayes Classifier Algorithm and to find out the level of accuracy in classification in determining promotion strategies. In this study the authors used 210 data as training data and 53 data as testing data for manual testing in excel and for testing using RapidMiner tools. Based on the results of the analysis in the research conducted, the results of predicting registration and non-registration quickly and accurately from tests carried out by comparing training data with data testing using RapidMiner tools obtained an accuracy rate of 92.45%.