Comparison of The Singular Spectrum Analysis and SARIMA for Forecasting Rainfall in Padang Panjang City

Main Article Content

Fadhira Vitasha Putri
Fadhilah Fitri
Yenni Kurniawati
Zilrahmi Zilrahmi

Abstract

Indonesia is an area with a tropical climate, so it has two seasons, namely the rainy season and the dry season. The rainy season lasts from November to March and during this period rainfall tends to be high in several areas. Padang Panjang City is one of the cities with the smallest area in West Sumatra Province, which has the nickname Rain City. This is because the city of Padang Panjang has cool air with a maximum air temperature of 26.1 °C and a minimum of 21.8 °C, so this city has a fairly high level of rainfall with an average of 300 to 400 mm/year. This article discusses rainfall forecasting for Padang Panjang City by comparing the Singular Spectrum Analysis and Seasonal Autoregressive Integrated Moving Average methods. The data used spans 8 years, from January 2016 to December 2023. Forecasting results are obtained from the best method selected based on the smallest Mean Absolute Percentage Error value. The Singular Spectrum Analysis method has a Mean Absolute Percentage Error value of 5.59% and Singular Spectrum Analysis and Seasonal Autoregressive Integrated Moving Average  has a value 7.43%. The best forecasting method is obtained by the Singular Spectrum Analysis method.

Downloads

Download data is not yet available.

Article Details

How to Cite
1.
Putri FV, Fitri F, Kurniawati Y, Zilrahmi Z. Comparison of The Singular Spectrum Analysis and SARIMA for Forecasting Rainfall in Padang Panjang City. IJSA [Internet]. 2025 Jun. 24 [cited 2025 Jul. 12];9(1):61-74. Available from: https://journal-stats.ipb.ac.id/index.php/ijsa/article/view/1252
Section
Articles

References

Alwi, W., Nurfadilah, K., & Munira. (2021). Penerapan Metode SARIMA untuk Peramalan Jumlah Pengunjung Wisata Taman Nasional Bantimurung Bulusaraung Maros. Journal of Mathematics: Theory and Applications, 3(1), 1–7. https://doi.org/10.31605/jomta.v3i1.1221

Fitri, F., & Rahmat, R. (2021). Comparison of SSA and SARIMA in Forecasting the Rainfall in Sumatera Barat. Journal of Physics: Conference Series, 1742(1). https://doi.org/10.1088/1742-6596/1742/1/012009

Jatmiko, Y. A., Rahayu, R. L., & Darmawan, G. (2017). Perbandingan Keakuratan Hasil Peramalan Produksi Bawang Merah Metode Holt-Winters Dengan Singular Spectrum Analysis (Ssa). Jurnal Matematika “MANTIK,” 3(1), 13. https://doi.org/10.15642/mantik.2017.3.1.13-24

Makridakis S, Wheelwright SC, H. R. (1997). 1 / the Forecasting Perspective. Forecasting Methods and Applications, 1–632.

Prianda, B. G., & Widodo, E. (2021). Perbandingan Metode Seasonal Arima Dan Extreme Learning Machine Pada Peramalan Jumlah Wisatawan Mancanegara Ke Bali. BAREKENG: Jurnal Ilmu Matematika Dan Terapan, 15(4), 639–650. https://doi.org/10.30598/barekengvol15iss4pp639-650

Purnama, D. I. (2021). Peramalan Curah Hujan Di Kabupaten Parigi Moutong Menggunakan Model Seasonal Autoregressive Integrated Moving Average (SARIMA). Jurnal Ilmiah Matematika Dan Terapan, 18(2), 136–147. https://doi.org/10.22487/2540766x.2021.v18.i2.15652

Purnama, E. (2022). Aplikasi Metode Singular Spectrum Analysis (SSA) pada Peramalan Curah Hujan di Provinsi Gorontalo. Jambura Journal of Probability and Statistics, 3(2), 161–170.

Susanti, N. E., Saputra, R., & Situmorang, I. A. (2024). Perbandingan Metode SARIMA, Double Exponential Smoothing dan Holt-Winter Additive dalam Peramalan Retail Sales Mobil Honda. Jurnal Sains Matematika Dan Statistika, 10(1), 58. https://doi.org/10.24014/jsms.v10i1.26375

Tresnawati, R., & Rosyidah. (2019). VALIDASI CURAH HUJAN KELUARAN METODE ANALISIS KORELASI KANONIK DENGAN SKENARIO TOPOGRAFI WILAYAH DI JAWA TENGAHValidation of Monthly Rainfall Prediction Taken from the Output of Canonical Correlation Analysis Using Area Topographical Scenarios in Centra J. Jurnal Media Informatika Budidarma, 6(3), 1297.