Property Rental Price Prediction Using the Extreme Gradient Boosting
Algorithm
Dublin Core
Title
Property Rental Price Prediction Using the Extreme Gradient Boosting
Algorithm
Algorithm
Subject
Rental Price; Prediction Model; Extreme Gradient Boosting; XGBoost.
Description
Online marketplace in the field of property renting like Airbnb is growing. Many property owners have begun renting out
their properties to fulfil this demand. Determining a fair price for both property owners and tourists is a challenge.
Therefore, this study aims to create a software that can create a prediction model for property rent price. Variable that
will be used for this study is listing feature, neighbourhood, review, date and host information. Prediction model is
created based on the dataset given by the user and processed with Extreme Gradient Boosting algorithm which then will
be stored in the system. The result of this study is expected to create prediction models for property rent price for
property owners and tourists consideration when considering to rent a property. In conclusion, Extreme Gradient
Boosting algorithm is able to create property rental price prediction with the average of RMSE of 10.86 or 13.30%.
their properties to fulfil this demand. Determining a fair price for both property owners and tourists is a challenge.
Therefore, this study aims to create a software that can create a prediction model for property rent price. Variable that
will be used for this study is listing feature, neighbourhood, review, date and host information. Prediction model is
created based on the dataset given by the user and processed with Extreme Gradient Boosting algorithm which then will
be stored in the system. The result of this study is expected to create prediction models for property rent price for
property owners and tourists consideration when considering to rent a property. In conclusion, Extreme Gradient
Boosting algorithm is able to create property rental price prediction with the average of RMSE of 10.86 or 13.30%.
Creator
Marco Febriadi Kokasih 1,*, Adi Suryaputra Paramita
Date
2020
Contributor
peri irawan
Format
pdf
Language
english
Type
text
Files
Collection
Citation
Marco Febriadi Kokasih 1,*, Adi Suryaputra Paramita, “Property Rental Price Prediction Using the Extreme Gradient Boosting
Algorithm,” Repository Horizon University Indonesia, accessed June 6, 2025, https://repository.horizon.ac.id/items/show/9218.
Algorithm,” Repository Horizon University Indonesia, accessed June 6, 2025, https://repository.horizon.ac.id/items/show/9218.