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Prediksi pembatalan pemesanan hotel menggunakan optimalisasi hiperparameter pada algoritme Random Forest

Prediction of hotel bookings cancellation using hyperparameter optimization on Random Forest algorithm

Department of Informatics, Universitas Muhammadiyah Malang. Jl. Raya Tlogomas No.246, Malang, Jawa Timur, Indonesia 65144, Indonesia

Received: 14 Jun 2020; Revised: 16 Nov 2020; Accepted: 27 Nov 2020; Published: 31 Jan 2021; Available online: 7 Dec 2020.
Open Access Copyright (c) 2021 The Authors. Published by Department of Computer Engineering, Universitas Diponegoro
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Citation Format:
Cancellation of hotel bookings by customers greatly influences hotel managerial decision making. To minimize losses by this problem, the hotel management made a fairly rigid policy 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 %. This study's results can be used as a model component in hotel managerial decision-making systems related to future bookings' cancellation.
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Keywords: classification; hyperparameter optimization; random forest
Funding: Universitas Muhammadiyah Malang, Indonesia

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