Peramalan Jumlah Produksi Kelapa Sawit Provinsi Kalimantan Timur Menggunakan Metode Singular Spectrum Analysis
Keywords:
Oil Palm Production, Forecasting, Singular Spectrum Analysis
Abstract
Singular spectrum analysis (SSA) is a nonparametric method that does not rely on assumptions such as stationary nature or residual normality. SSA separates time series data into its components, which are trend, seasonality, and error (noise). This study aimed to obtain forecasting results for the amount of oil palm production in East Kalimantan Province for the period January 2021 to December 2021 using SSA. Based on the results of the data analysis, in the process of forming the forecasting model with in-sample data, the parameter window length (L) was 24, which produced a MAPE value of 0.464%, and while the forecasting model validation process used out-sample data, it produced a MAPE value of 41.172%.
References
Dinas Perkebunan Provinsi Kalimantan Timur. (2020). Statistik Perkebunan Kalimantan Timur 2019. Samarinda: Dinas Perkebunan Provinsi Kalimantan Timur.
Fauzi, Y., Widyastuti, Y., Satyawibawa, I., & Hartono, R. (2002). Kelapa Sawit, Budidaya, Pemanfaatan Hasil dan Limbah Analisa, Usaha dan Pemasaran (Edisi Revisi). Jakarta: Penebar Swadaya.
Golyandina, N., & Zhigljavsky, A. (2013). Singular Spectrum Anlaysis for Time Series. New York: Springer.
Golyandina, N., Nekrutkin, V., & Zhigljavsky, A. A. (2001). Analysis of Time Series Structure: SSA and Related Techniques. Boca Raton: Chapman&Hall/CRC.
Hassani, H., & Mahmoudvand, R. (2018). Singular Spectrum Analysis With R. London: Palgrave Macmillan UK.
Ischak, R., Asrof, A., & Darmawan, G. (2018). Peramalan Rata-Rata Harga Beras di Tingkat Penggilingan Menggunakan Model Singular Spectrum Analysis (SSA). Prosiding Seminar Nasional Matematika dan Pendidikan Matematika (pp. 58-60). Purworejo: Pendidikan Matematika Universitas Muhammadiyah Purworejo.
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), 13-22.
Khaeri, H., Yulian, E., & Darmawan, G. (2018). Penerapan Metode Singular Spectrum Analysis (SSA) Pada Peramalan Jumlah Penumpang Kereta Api di Indonesia Tahun 2017. Jurnal Euclid, 5(1), 9-11.
Satriani, Nursalam, & Ibnas, R. (2020). Peramalan Indeks Harga Konsumen (IHK) di Sulawesi Selatan dengan Menggunakan Metode Singula Spectrum Analysis (SSA). Jurnal Matematika dan Statistika serta Aplikasinya, 8(1), 81-89.
Siregar, R. S., Prariesa, D., & Darmawan, G. (2017). Aplikasi Metode Singular Spectral Analysis (SSA) dalam Peramalan Pertumbuhan Ekonomi Indonesia Tahun 2017. Jurnal Matematika, 3(1), 1-14.
Suriani, N. (2019). Budi Daya Tanaman Kelapa Sawit. Jakarta: Bhuana Ilmu Komputer (Kelompok Gramedia).
Zhang, Q., Wang, B.-D., He, B., Peng, Y., & Ren, M.-L. (2011). Singular Spectrum Analysis and ARIMA Hybrid Model for Annual Runoff Forecasting. Water Resource Manage, 25(11), 2683-2703.
Zhigljavsky, A. (2010). Singular Spectrum Analysis for Time Series: Introduction to This Special Issue. Statistics and Its Interface, 3, 255-258
Fauzi, Y., Widyastuti, Y., Satyawibawa, I., & Hartono, R. (2002). Kelapa Sawit, Budidaya, Pemanfaatan Hasil dan Limbah Analisa, Usaha dan Pemasaran (Edisi Revisi). Jakarta: Penebar Swadaya.
Golyandina, N., & Zhigljavsky, A. (2013). Singular Spectrum Anlaysis for Time Series. New York: Springer.
Golyandina, N., Nekrutkin, V., & Zhigljavsky, A. A. (2001). Analysis of Time Series Structure: SSA and Related Techniques. Boca Raton: Chapman&Hall/CRC.
Hassani, H., & Mahmoudvand, R. (2018). Singular Spectrum Analysis With R. London: Palgrave Macmillan UK.
Ischak, R., Asrof, A., & Darmawan, G. (2018). Peramalan Rata-Rata Harga Beras di Tingkat Penggilingan Menggunakan Model Singular Spectrum Analysis (SSA). Prosiding Seminar Nasional Matematika dan Pendidikan Matematika (pp. 58-60). Purworejo: Pendidikan Matematika Universitas Muhammadiyah Purworejo.
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), 13-22.
Khaeri, H., Yulian, E., & Darmawan, G. (2018). Penerapan Metode Singular Spectrum Analysis (SSA) Pada Peramalan Jumlah Penumpang Kereta Api di Indonesia Tahun 2017. Jurnal Euclid, 5(1), 9-11.
Satriani, Nursalam, & Ibnas, R. (2020). Peramalan Indeks Harga Konsumen (IHK) di Sulawesi Selatan dengan Menggunakan Metode Singula Spectrum Analysis (SSA). Jurnal Matematika dan Statistika serta Aplikasinya, 8(1), 81-89.
Siregar, R. S., Prariesa, D., & Darmawan, G. (2017). Aplikasi Metode Singular Spectral Analysis (SSA) dalam Peramalan Pertumbuhan Ekonomi Indonesia Tahun 2017. Jurnal Matematika, 3(1), 1-14.
Suriani, N. (2019). Budi Daya Tanaman Kelapa Sawit. Jakarta: Bhuana Ilmu Komputer (Kelompok Gramedia).
Zhang, Q., Wang, B.-D., He, B., Peng, Y., & Ren, M.-L. (2011). Singular Spectrum Analysis and ARIMA Hybrid Model for Annual Runoff Forecasting. Water Resource Manage, 25(11), 2683-2703.
Zhigljavsky, A. (2010). Singular Spectrum Analysis for Time Series: Introduction to This Special Issue. Statistics and Its Interface, 3, 255-258
Published
2022-12-15
How to Cite
Siringoringo, M., Wahyuningsih, S., Purnamasari, I., & Arumsari, M. (2022). Peramalan Jumlah Produksi Kelapa Sawit Provinsi 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
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