Perbandingan Model Logistic Regression dan Artificial Neural Network pada Prediksi Pembatalan Hotel

Prediction for canceled booking hotels is an important part of hotel revenue management systems in the modern era. Because the predicted result can be used for the optimization of hotel performance. The application of machine learning will be very helpful for predicting canceled booking hotels becau...

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Main Authors: Moch Shandy Tsalasa Putra, Yufis Azhar
Format: Article
Language:English
Published: Universitas Islam Negeri Sunan Kalijaga Yogyakarta 2021-01-01
Series:JISKA (Jurnal Informatika Sunan Kalijaga)
Online Access:http://ejournal.uin-suka.ac.id/saintek/JISKA/article/view/1966
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author Moch Shandy Tsalasa Putra
Yufis Azhar
author_facet Moch Shandy Tsalasa Putra
Yufis Azhar
author_sort Moch Shandy Tsalasa Putra
collection DOAJ
description Prediction for canceled booking hotels is an important part of hotel revenue management systems in the modern era. Because the predicted result can be used for the optimization of hotel performance. The application of machine learning will be very helpful for predicting canceled booking hotels because machine learning can process complex data. In this research, the proposed methods are Artificial Neural Network (ANN) and Logistic Regression. Later it will be done five times experiments with hyperparameter tuning to see which method is the most optimal to do prediction canceled booking hotel. From five times experiments, experiments number five (logistic regression with GridSearchCV) is the most optimal for predicting canceled booking hotels, with 79.77% accuracy, 85.86% precision, and 55.07% recall.
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spelling doaj.art-b257145e613044d2bf0ea111b011db862023-09-02T19:00:12ZengUniversitas Islam Negeri Sunan Kalijaga YogyakartaJISKA (Jurnal Informatika Sunan Kalijaga)2527-58362528-00742021-01-016110.14421/jiska.2021.61-04Perbandingan Model Logistic Regression dan Artificial Neural Network pada Prediksi Pembatalan HotelMoch Shandy Tsalasa Putra0Yufis Azhar1Universitas Muhammadiyah MalangUniversitas Muhammadiyah MalangPrediction for canceled booking hotels is an important part of hotel revenue management systems in the modern era. Because the predicted result can be used for the optimization of hotel performance. The application of machine learning will be very helpful for predicting canceled booking hotels because machine learning can process complex data. In this research, the proposed methods are Artificial Neural Network (ANN) and Logistic Regression. Later it will be done five times experiments with hyperparameter tuning to see which method is the most optimal to do prediction canceled booking hotel. From five times experiments, experiments number five (logistic regression with GridSearchCV) is the most optimal for predicting canceled booking hotels, with 79.77% accuracy, 85.86% precision, and 55.07% recall.http://ejournal.uin-suka.ac.id/saintek/JISKA/article/view/1966
spellingShingle Moch Shandy Tsalasa Putra
Yufis Azhar
Perbandingan Model Logistic Regression dan Artificial Neural Network pada Prediksi Pembatalan Hotel
JISKA (Jurnal Informatika Sunan Kalijaga)
title Perbandingan Model Logistic Regression dan Artificial Neural Network pada Prediksi Pembatalan Hotel
title_full Perbandingan Model Logistic Regression dan Artificial Neural Network pada Prediksi Pembatalan Hotel
title_fullStr Perbandingan Model Logistic Regression dan Artificial Neural Network pada Prediksi Pembatalan Hotel
title_full_unstemmed Perbandingan Model Logistic Regression dan Artificial Neural Network pada Prediksi Pembatalan Hotel
title_short Perbandingan Model Logistic Regression dan Artificial Neural Network pada Prediksi Pembatalan Hotel
title_sort perbandingan model logistic regression dan artificial neural network pada prediksi pembatalan hotel
url http://ejournal.uin-suka.ac.id/saintek/JISKA/article/view/1966
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AT yufisazhar perbandinganmodellogisticregressiondanartificialneuralnetworkpadaprediksipembatalanhotel