Peramalan Curah Hujan di Banda Neira menggunakan Metode Autoregressive Integrated Moving Average (ARIMA)

Devan Florian Kastanya, Novita Serly Laamena

Abstract


Rainfall refers to the amount of rainwater that falls in an area in a certain period of time and usually measured in millimeters. Rainfall that is too high can cause disasters or losses for the wider community. Therefore, it is necessary to forecast rainfall for the future as an anticipation of bad events that may occur. One of the areas with high rainfall is Banda Neira Island. Rainfall forecasting can be done using time series modeling, one of which is ARIMA. This Research aims to determine the results of forecasting the amount of rainfall in Banda Neira using the ARIMA method. The data used for modeling is rainfall data for the period January 2018 to December 2022 sourced from the BPS of Maluku Province. Based on the research results, the best model  is ARIMA (1,0,0), and the results of rainfall forecasting from January to April 2023 respectively are 274.68 mm, 247.02 mm, 233.54 mm, 226.84 mm. When compared with past rainfall data, it can be said that the amount of rainfall in Banda Neira from January to April 2023 decreased by up to 10%.


Keywords


rainfall, forecasting, ARIMA

Full Text:

PDF

References


A. Ihwan, “Metode Jaringan Saraf Tiruan Propagasi Balik Untuk Estimasi Curah Hujan Bulanan di Ketapang Kalimantan Barat,” Pros. Semirata, vol. 1, no. 1, pp. 243–247, 2013.

S. Iriyanto, “ANALISIS POLA DAN AWAL MUSIM DI BANDA NAIRA,” Perpust. STMKG -ANALISIS POLA DAN AWAL MUSIM DI BANDA NAIRA, 2019.

S. Iriyanto, “ANALISIS KONDISI ATMOSFER SAAT HUJAN EKTREM DI BANDA NEIRA (Studi Kasus 23 Juli 2017),” Perpust. STMKG -, 2019.

L. Bakarbessy and N. S. Laamena, “Peramalan Indeks Pembangunan Manusia Menggunakan Metode Double Eksponential Smoothing,” Var. J. Stat. Its Appl., vol. 5, no. 1, pp. 67–78, 2023, doi: 10.30598/variancevol5iss1page67-78.

H. A. Maulana, “Pemodelan Deret Waktu Dan Peramalan Curah Hujan Pada Dua Belas Stasiun Di Bogor,” J. Mat. Stat. dan Komputasi, vol. 15, no. 1, p. 50, 2018, doi: 10.20956/jmsk.v15i1.4424.

D. Susilokarti, S. S. Arif, S. Susanto, and L. Sutiarso, “Studi Komparasi Prediksi Curah Hujan Metode Fast Fourier Transformation (Fft), Autoregressive Integrated Moving Average (Arima) Dan Artificial Neural Network (Ann),” J. Agritech, vol. 35, no. 02, p. 241, 2015, doi: 10.22146/agritech.9412.

U. Bengkulu, F. T. Series, and M. Chen, “PERBANDINGAN METODE ARIMA DENGAN FUZZY TIME SERIES MODEL CHEN PADA PERAMALAN CURAH HUJAN DI,” vol. 11, no. 3, pp. 154–166, 2024.

B. A. Safitri, A. Iriany, and N. W. S. Wardhani, “Perbandingan Akurasi Peramalan Curah Hujan dengan menggunakan ARIMA, Hybrid ARIMA-NN, dan FFNN di Kabupaten Malang,” Semin. Nas. Off. Stat., vol. 2021, no. 1, pp. 245–253, 2021, doi: 10.34123/semnasoffstat.v2021i1.853.

Novita Serly Laamena, “Pendekatan Model Generalized Space Time Autoregressive (GSTAR) Untuk Pemodelan Data Gempa,” Prosiding, vol. 1, no. 01, pp. 50–60, 2022, doi: 10.59134/prosidng.v1i01.74.

F. Fejriani, M. Hendrawansyah, L. Muharni, S. F. Handayani, and Syaharuddin, “Forecasting Peningkatan Jumlah Penduduk Berdasarkan Jenis Kelamin menggunakan Metode Arima,” J. Kajian, Penelit. dan Pengemb. Pendidik., vol. 8, no. 1 April, pp. 27–36, 2020.

Wulandari R.A and Gernowo R, “Metode Autoregressive Integrated Moving Average (ARIMA) dan Metode Adaptive Neuro Fuzzy Inference System (ANFIS) dalam Analisis Curah Hujan,” Berk. Fis., vol. 22, no. 1, pp. 41–48, 2019.

S. Deviana, Nusyirwan, D. Azis, and P. Ferdias, “Analisis Model Autoregressive Integrated Moving Average Data Deret Waktu Dengan Metode Momen Sebagai Estimasi Parameter,” J. Siger Mat., vol. 02, no. 02, pp. 57–67, 2021.

Tasna Yunita, “Peramalan Jumlah Penggunaan Kuota Internet Menggunakan Metode Autoregressive Integrated Moving Average (ARIMA),” J. Math. Theory Appl., vol. 1, no. 2, pp. 16–22, 2020, doi: 10.31605/jomta.v2i1.777.

N. Salwa, N. Tatsara, R. Amalia, and A. F. Zohra, “Peramalan Harga Bitcoin Menggunakan Metode ARIMA (Autoregressive Integrated Moving Average),” J. Data Anal., vol. 1, no. 1, pp. 21–31, 2018, doi: 10.24815/jda.v1i1.11874.




DOI: https://doi.org/10.15548/jostech.v5i1.9713

Refbacks

  • There are currently no refbacks.


Copyright (c) 2025 JOSTECH Journal of Science and Technology

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.