SISTEM REKOMENDASI PEMBELIAN HANDPHONE MENGGUNAKAN METODE NAIVE BAYES

This research aims to develop a mobile phone purchase recommendation system using the
Naive Bayes method to assist users or customers in selecting products that meet their needs. The
data used comes from www.kaggle.com with 1000 mobile phone data points divided into training
data (80%) and testing data (20%). The Naive Bayes model was trained using the training data
and evaluated using a Confusion Matrix to calculate accuracy, precision, recall, and F1-Score. The
testing results showed an accuracy of 99%, precision of 100%, recall of 98%, and an F1-Score of
99%. Data processing and algorithm implementation were carried out using Jupyter Notebook.
With a very good evaluation, this recommendation system is expected to assist users in choosing
the right mobile phone, reduce confusion, and enhance satisfaction in the purchasing process.