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All Journal Jurnal Statistika dan Matematika (Statmat)
Kailola, Juan
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Other

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Forecasting The Number of Rainy Days in Sorong City Using The Autoregressive Moving Average Method Kailola, Juan
STATMAT : JURNAL STATISTIKA DAN MATEMATIKA Vol 8 No 1 (2026)
Publisher : Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Pamulang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/sm.v8i1.55122

Abstract

A high number of rainy days can lead to disasters and economic losses, especially in sectors such as agriculture, transportation, and infrastructure. Therefore, forecasting the number of rainy days is essential as a preventive measure against potential adverse impacts. Sorong City is one of the regions in Indonesia that experiences significant rainfall throughout the year. This study aims to forecast the monthly number of rainy days in Sorong City using the Autoregressive Moving Average (ARMA) method. The data used in this study consist of the monthly number of rainy days recorded at the Meteorological Station of Sorong City from July 2017 to December 2024. The dataset from July 2017 to August 2024 was used to build the ARMA model, while the data from September to December 2024 served as the testing data to evaluate forecasting accuracy. The results show that the best model is ARMA (1,0) with MAPE of 22.56%. The forecast indicates that the number of rainy days from January 2025 to June 2026 remains stable at approximately 20 days per month.
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