PREDIKSI PEMBATALAN PEMESANAN HOTEL MENGGUNAKAN OPTIMALISASI HIPERPARAMETER PADA ALGORITMA RANDOM FOREST

Cancellation of hotel bookings by customers greatly influences hotel managerial decision making. In order to minimize losses due to this problem, the hotel management made a fairly rigidpolicy that could damage the reputation and business performance. Therefore, this study focuses on solving these problems using machine learning algorithms. To get the best model performance, hyperparameter optimization is applied to the random forest algorithm. It aims to obtain the best combination of model parameters in predicting hotel booking cancellations. The proposed model is proven to have the best performance with the highest accuracy results of 87%. The results of this study can be used as a model component in hotel managerial decision-making system related to the cancellation of future bookings