Property Rental Price Prediction Using the Extreme Gradient Boosting
Algorithm

Dublin Core

Title

Property Rental Price Prediction Using the Extreme Gradient Boosting
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%.

Creator

Marco Febriadi Kokasih 1,*, Adi Suryaputra Paramita

Date

2020

Contributor

peri irawan

Format

pdf

Language

english

Type

text

Files

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.