Business Closure Prediction Based on Users Rating and Review Using H2O
Predicting business closure refers to the process of analyzing various factors and making predictions about the likelihood that a business will close. Closing a business does not only affect business owner, but it also has an impact on employees. There have been many studies conducted on predicting business closures based on managerial or economic factors, but research discussing predicting business closures based on customer reviews or ratings is still limited. Prediction of business closures is made to assist business owner in reducing the risk of loss and business closure. In this research, business closure predictions are made based on the combination between customer ratings and review data. Merging these two data is done to see whether it can increase the level of accuracy of the predicted results of business closures compared to rating or review data alone. Predictions are made using a deep learning framework, H20, which can prevent the model from experiencing overfitting.
Authors
- Muhammad Fermi Pasha (ORCID: https://orcid.org/0000-0002-9848-8950)
- Ronsen Purba
- Enjelin
Publication Details
- Published
- 2024-09-12
- DOI
- https://doi.org/10.1109/ictiia61827.2024.10761845
- Primary Topic
- Customer churn and segmentation
- Type
- article
- Field-Weighted Citation Impact
- 0.00