Jurnal Statistika dan Matematika (Statmat)
Vol 8 No 1 (2026)

Forecasting The Number of Rainy Days in Sorong City Using The Autoregressive Moving Average Method

Kailola, Juan (Unknown)



Article Info

Publish Date
30 Apr 2026

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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Journal Info

Abbrev

sm

Publisher

Subject

Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Other

Description

P-ISSN : 2655-3724 E-ISSN : 2720-9881 Jurnal Statmat UNPAM: Jurnal Statistika dan Matematika Universitas Pamulang is a means of publication of scientific articles and research with concentrations of Statistics, Pure Mathematics, Applied Mathematics, Computational Mathematics, Educational ...