Implementasi Algoritma Decision Tree dan Naïve Bayes Untuk Klasifikasi Sentimen Terhadap Kepuasan Pelanggan Starbucks - Tiyas Asih Qurnia Putri; Agung Triayudi; Rima Tamara Aldisa (Forum Kerjasama Pendidikan Tinggi (FKPT), 2023)
Indonesia is included in the category of countries with the largest population in the world, this situation is a business opportunity for entrepreneurs who enter the coffee shop industry market. Researchers utilize one of the grouping methods, namely data mining classification in order to help business entities to identify different groups in the Starbucks customer satisfaction database. The purpose of this research is to be able to group categories into 3 classes, namely satisfied, quite satisfied and dissatisfied using the Decision Tree & Naive Bayes algorithm. So that it can find out public opinion on Starbucks customer satisfaction, in this study the aim was to obtain accuracy, precision and recall values and find out the best algorithm for data mining classification of Starbucks customer satisfaction. In this study using test data obtained from tweets with the keyword