Application of singular spectrum analysis (SSA) method on forecasting train passengers data in sumatera
Abstract
A time series is a series of observations of a variable that is collected, recorded, or observed over a period of time in sequence. Singular Spectrum Analysis is a powerful method to analyze time series data by decomposing the original time series data into several small components that can be identified, such as trend, periodic, and noise components. One of the datasets that can be used is data on the number of train passengers in Sumatera in 2013–2022. In this study, the Singular Spectrum Analysis method is used to forecast the number of train passengers in Sumatera in 2013–2022. The best Singular Spectrum Analysis model in this study was obtained at a window length of 22 and a number of groups of 8, with a MAPE value of 19.55%.
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Andhika, G. B., Sumarjaya, I. W., & Srinadi, I. G. A. M. (2020). Peramalan nilai tukar petani menggunakan metode singular spectrum analysis. E-Jurnal Matematika, 9(3), 171. https://doi.org/10.24843/MTK.2020.v09.i03.p295
Badan Pusat Statistik. (2022). Jumlah penumpang kereta api (ribu orang). Retrieved November 17, 2023, from https://www.bps.go.id/ indicator/17/72/1/jumlah-penumpang-kereta-api.html
Chang, P.-C., Wang, Y.-W., & Liu, C.-H. (2007). The development of a weighted evolving fuzzy neural network for pcb sales forecasting. Expert Systems with Applications, 32(1), 86–96. https://doi.org/10.1016/j.eswa.2005.11.021
Golyandina, N., & Zhigljavsky, A. (2013). Singular spectrum analysis for time series (1st ed.). Springer.
Golyandina, N., & Zhingljavsky, A. (2020). Singular spectrum analysis for time series (2nd ed.). Springer.
Heizer, J., & Render, B. (2011). Manajemen operasi. Salemba Empat.
Hidayat, K. W., Wahyuningsih, S., & Nasution, Y. N. (2020). Pemodelan jumlah titik panas di provinsi kalimantan timur dengan metode singular spectrum analysis. Jambura Journal of Probability and Statistics, 1(2), 78–88. https://doi.org/10.34312/jjps.v1i2.7287
Niu, Y., Guo, J., Yuan, J., Zhu, C., Zhou, M., Liu, X., & Ji, B. (2020). Prediction of sea level change in Japanese coast using singular spectrum analysis and auto regression moving average. Chinese Journal of Geophysics, 63(9), 3263–3274.
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.
Satriani, S., & Ibnas, R. (2020). Peramalan indeks harga konsumen (ihk) di sulawesi selatan dengan menggunakan metode singular spectrum analysis (ssa). Jurnal MSA (Matematika Dan Statistika Serta Aplikasinya), 8(1), 82–89. https://doi.org/10.24252/msa.v8i1.17441
Sergio, A., Wahyuningsih, S., & Siringoringo, M. (2023). Peramalan inflasi kota balikpapan menggunakan metode singular spectrum analysis. Jurnal EKSPONENSIAL, 14(1), 21–30.
Siringoringo, M., Wahyuningsih, S., Purnamasari, I., & Arumsari, M. (2022). Peramalan jumlah produksi kelapa sawit kalimantan timur menggunakan metode singular spectrum analysis. VARIANSI: Journal of Statistics and Its Application on Teaching and Research, 4(3), 162–172. https://doi.org/10.35580/variansiunm46
Sodiqin, M. A., Sulandari, W., & Respatiwulan. (2021). The application of singular spectrum analysis method in forecasting the number of foreign tourists visit to special capital region of jakarta. Jurnal Riset Dan Aplikasi Matematika (JRAM), 5(2), 92–102.
Utami, N. A. G., Sulandari, W., & Handajani, S. S. (2021). Peramalan curah hujan bulanan di pos hujan jatisrono dengan metode singular spectrum analysis (ssa). Prosiding Seminar Nasional Aplikasi Sains & Teknologi.
Wijayanti, L. N., & Kartikasari, M. D. (2023). Application of singular spectrum analysis method in forecasting indonesia composite data. BAREKENG: Jurnal Ilmu Matematika Dan Terapan, 17(1), 0513–0526. https://doi.org/10.30598/barekengvol17iss1pp0513-0526
DOI: http://dx.doi.org/10.24042/djm.v6i3.19040
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