Prediction of Monthly Rainfall with Using Monte Carlo Simulation in the Medan City Area

The climate in Indonesia, which is a tropical region, is always uncertain and makes it difficult to predict weather conditions. Weather conditions can be influenced by rainfall, air temperature, wind speed, air humidity and light radiation intensity. Rainfall is relatively high and varies throughout the year, the average monthly rainfall is around 150-300 mm in the rainy season and 50-100 mm in the dry season. There are several characteristics of rainfall, namely convective rain, frontal rain and orographic rain. For this reason, a method is needed that can solve problems in predicting monthly rainfall properties using the Monte Carlo simulation method. From this study, the results of the prediction of rainfall properties were obtained with 36 data from 2021 to 2024 which had a MAPE test result of 12.28%. The test results came from the average calculation carried out on the Monte Carlo method prediction with 5 variables.

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Publication Details

Journal
Jurnal Sisfokom (Sistem Informasi dan Komputer)
Published
2024-11-25
DOI
https://doi.org/10.32736/sisfokom.v13i3.2307
Primary Topic
Data Mining and Machine Learning Applications
Type
article
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article

Prediction of Monthly Rainfall with Using Monte Carlo Simulation in the Medan City Area

Hendra Cipta, Arini Arini
Jurnal Sisfokom (Sistem Informasi dan Komputer)
Data Mining and Machine Learning Applications
article

Prediction of Monthly Rainfall with Using Monte Carlo Simulation in the Medan City Area

Hendra Cipta, Arini Arini
article en

Abstract

The climate in Indonesia, which is a tropical region, is always uncertain and makes it difficult to predict weather conditions. Weather conditions can be influenced by rainfall, air temperature, wind speed, air humidity and light radiation intensity. Rainfall is relatively high and varies throughout the year, the average monthly rainfall is around 150-300 mm in the rainy season and 50-100 mm in the dry season. There are several characteristics of rainfall, namely convective rain, frontal rain and orographic rain. For this reason, a method is needed that can solve problems in predicting monthly rainfall properties using the Monte Carlo simulation method. From this study, the results of the prediction of rainfall properties were obtained with 36 data from 2021 to 2024 which had a MAPE test result of 12.28%. The test results came from the average calculation carried out on the Monte Carlo method prediction with 5 variables.

Jurnal Sisfokom (Sistem Informasi dan Komputer)Vol. 13(3)
Universitas Islam Negeri Sumatera Utara (ID)
Climate action
Openalex Percentile: Top 67%
Data Mining and Machine Learning Applications
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Prediction of Monthly Rainfall with Using Monte Carlo Simulation in the Medan City Area — Hendra Cipta, Arini Arini · Jurnal Sisfokom (Sistem Informasi dan Komputer) (2024) | TGRS Research Map | TGRS