Cocoa price prediction in North Sumatra using Singular Spectrum Analysis (SSA) Algorithm

Authors

  • Sintia Fransiska Universitas Islam Negeri Sumatera Utara
  • Ismail Husein Universitas Islam Negeri Sumatera Utara Medan

DOI:

10.33395/sinkron.v8i3.12559

Keywords:

Singular Spectrum Analysis, Prediction, MAPE

Abstract

The implementation of agricultural development is basically aimed at increasing the welfare of the people, especially farmers, providing a source of foreign exchange through exports, supplying food and industrial raw materials, alleviating poverty, providing employment and improving people's income. Cocoa is a leading commodity which is a source of income for farmers in North Sumatra. Price fluctuations sometimes make farmers suffer losses, so it is necessary to make a cocoa price prediction to anticipate future losses. This study aims to determine the prediction results of cocoa prices in North Sumatra in 2023 and the accuracy of the method used. The results of the study obtained the prediction of cocoa prices in North Sumatra Province in 2023 using the Singular Spectrum Analysis (SSA) method from January to December, respectively, Rp. 34876 in January, February prediction of Rp. 33967, March prediction of Rp. 33446, in April RP 33725, prediction in May of Rp. 33986, prediction in June of Rp 33916, in July Rp. 34196, predictionin August of Rp. 34841, prediction in September of Rp. 35228, in October of Rp. 3479, in November Rp 344517, the December prediction is Rp 34770 with a prediction accuracy level based on the standard MAPE value of 0.96%. The MAPE value obtained indicates that the SSA approach with Windows length 18 and 14 groups is very accurate for prediction cocoa price in North Sumatra Province because it is less than 10% and close to 0%.

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Author Biography

Sintia Fransiska, Universitas Islam Negeri Sumatera Utara

 

 

References

BPS. (2021). Statistik Kakao Indonesia. Jakarta: Badan Pusat Statistik.

E.P.Box, G., Jenkins, G. M., C.Reinsel, G., & M.Ljung, G. (2016). Time Series Analysis Forecasting and Control. New Jersey: Jhon Wiley & Sons.

Golyandina, & Zhigljavsky. (n.d.). Singular Spectrum analysis for Time Series. STAT ME.

Hajjah, A., & Nora Marlim, Y. (2021). Analisis Error Terhadap Peramalan Data Penjualan Error Analysis Toward Sales Data Forecasting. Februari, 20(1), 1–9.

Hardi, D. T., Safitri, D., & Rusgiyono, A. (2019). Peramalan Produk Domestik Bruto (Pdb) Sektor Pertanian, Kehutanan, Dan ‎Perikanan Menggunakan Singular Spectrum Analysis (Ssa). Jurnal Gaussian, 8(1), 68–80. doi:10.14710/j.gauss.v8i1.26623

Hasnudi, & Iskandar, S. (2005). Rencaan Stategis Pembangunan Perkebunan di Provinsi Sumatera Utara Tahun 2005-2012. Medan: Lecturer Papers Fakultas Pertanian Universitas Sumatera Utara.

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. doi:10.34312/jjps.v1i2.7287

Idrus, R. A., Ruliana, & Aswi. (2022). Penerapan Metode Singular Spectrum Analysis dalam Peramalan Jumlah Produksi Beras di Kabupaten Gowa. VARIANSI: Journal of Statistics and Its Application on Teaching and Research, 4(2), 49–58. doi:10.35580/variansiunm40

Irwan, Adnan Sauddin, & Anita Kaimuddin. (2022). Proyeksi Produksi Padi Kabupaten Pinrang Dengan Metode Singular Spectrum Analysis. Jurnal MSA ( Matematika Dan Statistika Serta Aplikasinya ), 10(1), 100–109. doi:10.24252/msa.v10i1.29869

Jenderal, S. (2007). Gambaran Sekilas Industri Kakao.

Karim, I., Fatmawaty, Anas, & Wulandari, E. (2020). Agribisnis Kakao. Yogyakarta: Deepublish.

Kusumasturi, A., Khoiron, A. M., & Achmadi, T. A. (2020). Metode Penelitian Kuantitatif. Yogyakarta: Deepublish.

Misnani. (2008). Physico-Chemical Changes During Cocoa Fermentation and Key Enzymes Involved. Review Penelitian Kopi dan Kakao.

Prasetya, H., & Lukiastuti, F. (2009). Manajemen Operasi. Yogyakarta: MedPress.

Riyanto, S., & Putera, A. R. (n.d.). Metode Riset Penelitian Kesehatan dan Sains. Yogyakarta: Deepublish.

Ruhiat, D., Andiani, D., & Kamilah, W. N. (2020). Forecasting Data Runtun Waktu Musiman Menggunakan Metode Singular Spectrum Analysis (Ssa). Teorema: Teori Dan Riset Matematika, 5(1), 47. doi:10.25157/teorema.v5i1.3286

Rusono, N., Sunari, A., Candradijaya, A., Martino, I., & Tejaningsih. (2013). Analisis Nilai Tukar Petani (NTP) sebagai bahan penyusunan RPJMN Tahun 2015-2019. Jakarta: Kementrian Perencanaan Pembangunan Nasional.

Sahabannur. (2018). Teknologi Fermentasi Biji Kakao. Bogor: IPB Press.

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How to Cite

Fransiska, S. ., & Husein, I. (2023). Cocoa price prediction in North Sumatra using Singular Spectrum Analysis (SSA) Algorithm. Sinkron : Jurnal Dan Penelitian Teknik Informatika, 7(3), 1587-1598. https://doi.org/10.33395/sinkron.v8i3.12559