Peramalan Jumlah Curah Hujan di Kota Pariaman Menggunakan Metode ARIMA
Authors
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Deya Junida Putri
Universitas Negeri Padang
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Zamahsary Martha
Universitas Negeri Padang
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Admi Salma
Universitas Negeri Padang
DOI:
https://doi.org/10.36312/jar.v5i3.6451Keywords:
Curah hujan; Kota Pariaman; Deret Waktu; Peramalan; ARIMAAbstract
Curah hujan merupakan salah satu unsur iklim yang berpengaruh terhadap berbagai sektor, seperti pertanian, perikanan, kesehatan, transportasi serta pengelolaan sumber daya di Indonesia. Kota Pariaman yang merupakan wilayah pesisir dengan tingkat kerentanan banjir yang memerlukan sistem peramalan jumlah curah hujan yang akurat sebagai antisipasi dampak bencana yang ditimbulkan dan untuk mendukung perencanaan pembangunan. Penelitian ini bertujuan untuk melakukan peramalan data deret waktu jumlah curah hujan di Kota Pariaman dengan menggunakan metode Autoregressive Integrated Moving Average (ARIMA). Penelitian ini menggunakan data sekunder yang diambil dari website Badan Pusat Statistik (BPS) Kota Pariaman terkait jumlah curah hujan dari Januari 2020 sampai Desember 2024. Berdasarkan hasil analisis, diperoleh model terbaik yaitu model ARIMA (2,0,2) dengan nilai MSE terkecil dan residual yang berdistribusi normal. Hasil analisis juga menunjukkan nilai MAPE sebesar 6,81% artinya model ARIMA (2,0,2) sudah sangat akurat digunakan. Hasil peramalan ini diharapkan dapat dijadikan dasar pengambilan keputusan bagi pemerintah dan masyarakat dalam mengantisipasi dampak bencana dan mendukung perencanaan pembangunan di Kota Pariaman.
Rainfall is one of the climate elements that affect various sectors, such as agriculture, fisheries, health, transportation and resource management in Indonesia. Pariaman City, which is a coastal area that has a high vulnerability to flood disasters, requires an accurate rainfall forecasting system to anticipate the impact of disasters caused and to support development planning. This study aims to forecast time series data on the amount of rainfall in Pariaman city using the Autoregressive Integrated Moving Average (ARIMA) method. This research uses secondary data taken from the Pariaman City Statistics Agency (BPS) website regarding the amount of rainfall from January 2020 to December 2024. Based on the results of the analysis, the best model is the ARIMA (2,0,2) model with the smallest MSE value and normally distributed residuals. The analysis results also show a MAPE value of 6.81%, meaning that the ARIMA (2,0,2) model is very accurate to use. The results of this forecasting are expected to be used as a basis for decision making for the supporting development planning in Pariaman City.
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Copyright (c) 2026 Deya Junida Putri, Zamahsary Martha, Admi Salma
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