Peramalan Curah Hujan dengan Pengelompokan Bulan Menggunakan Metode Double Exponential Smoothing dari Brown
DOI:
https://doi.org/10.26418/justin.v10i4.47167Keywords:
Rainfall, Double exponential smoothing, Brown, Forecasting, Month groupingAbstract
It is important to know the future rainfall, the way is to predict rainfall. By knowing future rainfall, development strategies such as irrigation, dams, urban drainage, harbour docks, agriculture, and even disaster mitigation strategies will be right on target. The purpose of this study is to predict the rainfall for Boyolali Regency and Surakarta City, Central Java in 2020-2021 with Brown's double exponential smoothing method. The type of data used is secondary data, which is obtained from the Meteorology, Climatology and Geophysics Agency of Semarang Climatology Station. The smoothing value, alpha, used in each month was varies, because the rainfall data is grouped first based on the same month, before it was forecasted. The results showed that the highest rainfall in 2020 was 490.73 mm (April) and the lowest was 3.25 mm (August). While for 2021, the highest rainfall was 521.37 (April) and the lowest was 3.25 mm (August), with an MSE of 14731.56, RMSE of 121.37, MAD of 97.42, and SSE of 176778.69.References
A. K. Hidayat and Empung, “Analisis Curah Hujan Efektif dan Curah Hujan dengan Berbagai Periode Ulang untuk Wilayah Kota Tasikmalaya dan Kabupaten Garut,†J. Siliwangi, vol. 2, no. 2, pp. 121–126, 2016.
F. Prawaka, A. Zakaria, and S. Tugiono, “Analisis Data Curah Hujan yang Hilang Dengan Menggunakan Metode Normal Ratio, Inversed Square Distance, Dan Cara Rata-Rata Aljabar (Studi Kasus Curah Hujan Beberapa Stasiun Hujan Daerah Bandar Lampung),†J. Rekayasa Sipil dan Desain, vol. 4, no. 3, pp. 397–406, 2016.
H. Chandra and H. Suprapto, “Sistem Informasi Intensitas Curah Hujan di Daerah Ciliwung Hulu,†J. Ilm. Inform. Komput., vol. 21, no. 3, pp. 45–52, 2016.
S. F. Hilmi and E. Nurjani, “Hubungan Variabilitas Curah Hujan Terhadap Kejadian Banjir di Wilayah Bandung,†J. Bumi Indones., vol. 8, no. 4, pp. 1–11, 2019.
I. N. Purnama and A. A. A. P. Ardyanti, “Peramalan Kunjungan Wisatawan di Obyek Wisata Bedugul Menggunakan Algoritma Fuzzy Time Series,†Smartics J., vol. 3, no. 2, pp. 55–58, 2017.
E. Pujiati, D. Yuniarti, and R. Goejantoro, “Peramalan dengan Menggunakan Metode Double Exponential Smoothing dari Brown (Studi Kasus: Indeks Harga Konsumen (IHK) Kota Samarinda),†J. Eksponensial, vol. 7, no. 1, pp. 33–40, 2016.
H. D. E. S. Sinaga and N. Irawati, “Perbandingan Double Moving Average dengan Double Exponential Smoothing pada Peramalan Bahan Medis Habis Pakai,†Jurteksi (Jurnal Teknol. dan Sist. Informasi), vol. IV, no. 2, pp. 197–204, 2018.
Y. L. Saputra and Ekojono, “Sistem Informasi Prediksi Jumlah Wisatawan pada Jawa Timur Park Group Kota Wisata Batu Menggunakan Metode Forecasting,†J. Inform. Polinema, vol. 2, no. 3, pp. 127–131, 2016.
F. Andrian, S. Martha, and S. Rahmayuda, “Sistem Peramalan Jumlah Mahasiswa Baru Menggunakan Metode Triple Exponential Smoothing,†Coding J. Komput. dan Apl., vol. 08, no. 01, pp. 112–121, 2020.
A. Aden and A. L. Al Jauzi, “Prediksi Jumlah Siswa Baru yang Mendaftar Menggunakan Eksponensial Ganda Satu-Parameter dari Brown,†Statmat J. Stat. dan Mat., vol. 1, no. 2, pp. 17–27, 2019.
S. Putramulyo and S. Alaa, “Prediksi Curah Hujan Bulanan di Kota Samarinda Menggunakan Persamaan Regresi dengan Prediktor Data Suhu dan Kelembapan Udara,†Eig. Math. J., vol. 2, no. 2, pp. 13–16, 2018.
S. Andayani and Y. Astuti, “Prediksi Kejadian Penyakit Tuberkulosis Paru Berdasarkan Usia Di Kabupaten Ponorogo Tahun 2016-2020,†Indones. J. Heal. Sci., vol. 1, no. 2, pp. 29–33, 2017.
K. D. Hartomo and Y. Nataliani, “A new model for learning-based forecasting procedure by combining k-means clustering and time series forecasting algorithms,†PeerJ Comput. Sci., vol. 7, no. e534, pp. 1–29, 2021.
N. Iksan, Y. P. Putra, and E. D. Udayanti, “Regresi Linier untuk Prediksi Permintaan Sparepart Sepeda Motor,†Inf. Technol. Eng. Journals, vol. 03, no. 02, pp. 3–7, 2018.
K. Ariansyah, “Proyeksi Pertumbuhan Jumlah Pelanggan Radio Trunking Terrestrial Dengan Analisis Runtut Waktu,†Bul. Pos dan Telekomun., vol. 11, no. 1, pp. 77–92, 2013.
I. C. R. Drajana, “Metode Support Vector Machine dan Forward Selection Prediksi Pembayaran Pembelian Bahan Baku Kopra,†Ilk. J. Ilm., vol. 9, no. 2, pp. 116–123, 2017.
F. R. Lumbanraja, R. S. Sani, D. Kurniawan, and A. R. Irawati, “Implementasi Metode Support Vector Machine Dalam Prediksi Persebaran Demam Berdarah di Kota Bandar Lampung,†J. Komputasi, vol. 7, no. 2, pp. 63–73, 2019.
Downloads
Published
Issue
Section
License
Copyright (c) 2022 JUSTIN (Jurnal Sistem dan Teknologi Informasi)

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
The author owns the copyright in his paper and agrees to publish his paper to JUSTIN by giving the rights to the first publication of his paper which is simultaneously licensed under the Creative Commons Attribution License, namely the Similar International 4.0 license (CC BY-NC-SA 4.0).

This is a human-readable summary of (and not a substitute for) the license. Disclaimer.
You are free to:Share "” copy and redistribute the material in any medium or format
Adapt "” remix, transform, and build upon the material
The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
Attribution "” You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
NonCommercial "” You may not use the material for commercial purposes.
ShareAlike "” If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
No additional restrictions "” You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation.
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.