Universitas Stikubank (Unisbank) Semarang Repository

Rainfall prediction using Extreme Gradient Boosting

Muchamad Taufiq, Anwar and Edy, Winarno and Wiwien, Hadikurniawati Rainfall prediction using Extreme Gradient Boosting. Annual Conference on Science and Technology (ANCOSET 2020).

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Rainfall greatly affects human life in various sectors including agriculture, transportation, etc. and also can affect natural disasters such as drought, floods, and landslides. This situation prompts us to build an accurate rainfall prediction model so that prescriptive measures can be made. Previous research on rainfall prediction uses models that have their limitations and thus produce poor performance. This study aims to build a multivariate rainfall prediction model using the best performing technique to date namely the Extreme Gradient Boosting. This model is built based on 7 years of historical weather data collected by the weather station. The result had demonstrated that the model is capable of producing accurate predictions for daily rainfall estimates with training RMSE of 2.7 mm and the testing MAE of 8.8 mm.

Item Type: Article
Subjects: H Social Sciences > H Social Sciences (General)
Q Science > Q Science (General)
Faculty / Institution: Fakultas Teknologi Informasi
Depositing User: Fakultas Ekonomi
Date Deposited: 07 Oct 2022 03:27
Last Modified: 07 Oct 2022 03:27
URI: https://eprints.unisbank.ac.id/id/eprint/8810

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