Predicting the outcome of purchasing a hotel package to assist policymakers using machine learning
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022.
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Brac University
2023
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| 在线阅读: | http://hdl.handle.net/10361/18701 |
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10361-187012023-07-10T21:03:17Z Predicting the outcome of purchasing a hotel package to assist policymakers using machine learning Islam, Zahedul Shetu, Tahsina Alam Bhattacharjee, Atulan Mohima, Jannatul Ferdous Chakrabarty, Amitabha Mukta, Jannatun Noor Department of Computer Science and Engineering, Brac University Prediction Hotel package Policymakers Deep learning Machine learning This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022. Cataloged from PDF version of thesis. Includes bibliographical references (pages 38-39). Given the growing and massive shock to the hotel industry, the coronavirus (COVID- 19) outbreak has generated an unexpected problem. The hotel industry is currently facing a big obstacle during the COVID period, where strategies designed to promote sustainability will play an essential role for the industry. Hotel policymakers would need to learn from the COVID-19 issue in order to increase sales, improve crisis management policies, and better prepare targets and the industry as a whole to respond to unforeseen situations. It would be preferable if the hotel sector used information and technology and focused on automated ways of learning and forecasting from historical data. The objective of this research is to study customer information in order to make a recommendation to the policy maker and marketing team, as well as to develop a model to predict who will buy the newly launched vacation package. It will assist the hotel industry in enabling and establishing a viable business model for growing their customer base. As a result, we’re adopting machine learning to predict which customers will be interested in purchasing the hotel package. A survey was used to gather data for this study. The data was evaluated to uncover key elements for our study, and we employed seven algorithms, namely, Random Forest Classifier, K Neighbors Classifier, Naive Bayes, AdaBoost, Support Vector Machine, Logistic Regression, and Gradient Boosting algorithm, to predict potential customers based on those features. We have obtained an accuracy of 95% while also reducing the number of false negatives by using the Gradient Boosting Classifier, Support Vector Machine, Random Forest Classifier, Naive Bayes, Logistic Regression. Our findings show that, without a team of analysts, our analysis and suggested approach can provide the finest insight to policymakers to help them make better decisions. Zahedul Islam Tahsina Alam Shetu Atulan Bhattacharjee Jannatul Ferdous Mohima B. Computer Science 2023-07-10T05:34:50Z 2023-07-10T05:34:50Z 2022 2022-05 Thesis ID 18101209 ID 18101174 ID 18101521 ID 17301009 http://hdl.handle.net/10361/18701 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 39 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Prediction Hotel package Policymakers Deep learning Machine learning |
| spellingShingle |
Prediction Hotel package Policymakers Deep learning Machine learning Islam, Zahedul Shetu, Tahsina Alam Bhattacharjee, Atulan Mohima, Jannatul Ferdous Predicting the outcome of purchasing a hotel package to assist policymakers using machine learning |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022. |
| author2 |
Chakrabarty, Amitabha |
| author_facet |
Chakrabarty, Amitabha Islam, Zahedul Shetu, Tahsina Alam Bhattacharjee, Atulan Mohima, Jannatul Ferdous |
| format |
Thesis |
| author |
Islam, Zahedul Shetu, Tahsina Alam Bhattacharjee, Atulan Mohima, Jannatul Ferdous |
| author_sort |
Islam, Zahedul |
| title |
Predicting the outcome of purchasing a hotel package to assist policymakers using machine learning |
| title_short |
Predicting the outcome of purchasing a hotel package to assist policymakers using machine learning |
| title_full |
Predicting the outcome of purchasing a hotel package to assist policymakers using machine learning |
| title_fullStr |
Predicting the outcome of purchasing a hotel package to assist policymakers using machine learning |
| title_full_unstemmed |
Predicting the outcome of purchasing a hotel package to assist policymakers using machine learning |
| title_sort |
predicting the outcome of purchasing a hotel package to assist policymakers using machine learning |
| publisher |
Brac University |
| publishDate |
2023 |
| url |
http://hdl.handle.net/10361/18701 |
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