Penerapan Metode Fuzzy Time Series (FTS) Cheng dan Markov-Chain untuk Peramalan Indonesia Crude Oil Price (ICP)

Deby Fakhriyana, Indira Ihnu Brilliant

Abstract

In Indonesia, crude oil plays a significant role in the country’s economy as it serves as a source of income and meets the country's energy needs. Therefore, fluctuations in crude oil prices have a significant impact on the economic activities of the society. Forecasting the price of Indonesian crude oil is thus crucial. The international price of crude oil in Indonesia is known as the Indonesian Crude Oil Price (ICP). One commonly used statistical method for forecasting is the ARIMA method. However, the ARIMA method has certain assumptions that need to be fulfil, and many real-world data cannot meet these assumptions. Hence, forecasting using the Fuzzy Time Series (FTS) method, which does not rely on assumptions, is employed. Some popular FTS methods include the Cheng FTS method and the Markov Chain FTS method. This study implements the Cheng FTS and Markov Chain FTS methods on the ICP data from May 2018 to June 2023 to determine the most appropriate method for forecasting. The analysis results using the Cheng FTS method on the testing data yield a Mean Absolute Percentage Error (MAPE) value of 4,083%, while the Markov Chain FTS method has MAPE value of 4,585%. The Cheng FTS method selected as the appropriate model for forecasting the ICP data since it has a smaller MAPE value. Using the Cheng FTS method, the predicted ICP value for July 2023 is US$72,907 per barrel.

Keywords: ICP; FTS Cheng; FTS Markov Chain; MAPE

Full Text:

PDF

References

C. Tjahjaprijadi, "Dampak Penurunan Indonesian Crude Oil Price Terhadap Pertumbuhan Ekonomi Indonesia," 2015. [Online]. Available: https://fiskal.kemenkeu.go.id/kajian/2015/12/31/145740273503251-dampak-penurunan-indonesian-crude-oil-price-terhadap-pertumbuhan-ekonomi-indonesia.

W. Bank, "Indonesia Economic Prospects Halving Poverty," 2021. [Online]. Available: https://www.worldbank.org/en/country/indonesia/publication/indonesia-economic-prospects-halving-poverty-by-2021-123414.

M. Wati, Haviluddin, A. Masyudi, A. Septiarini and H. R. Hatta, "Autoregressive Integrated Moving Average (ARIMA) Model for Forecasting Indonsesian Crude Oil Price," Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI), vol. 9, no. 3, pp. 720-730, 2023.

D. Suryani, M. Fadhilla and A. Labellapansa, "Indonesian Crude Oil Price (ICP) Prediction Using Multiple Linear Regression Algorithm," Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), vol. 6, no. 6, pp. 1057-1063, 2022.

Vivianti, M. K. Aidid and M. Nusrang, "Implementasi Metode Fuzzy Time Series untuk Peramalan JUmalh Pengunjung di Benteng Fort Rotterdam," VARIANSI: Journal of Statistics and Its Application on Teaching and Research, vol. 2, no. 1, pp. 1-12, 2020.

M. Y. Fathoni, "Implementasi Metode Fuzzy Time Series Cheng untuk Prediksi Konsentrasi gas NO2 di Udara," Jurnal Sistem Informasi Bisnis, vol. 7, no. 1, pp. 17-23, 2017.

Sumartini, M. N. Hayati and S. Wahyuningsih, "Peramalan Mengguankan Metode Time Series Cheng," Jurnal EKSPONENSIAL, vol. 8, no. 1, 2017.

S. I. J. Telaumbanua and D. Febrian, "Comparison of Fuzzy Time Series Markov Chain and Fuzzy Time Series Lee in North Sumatra IMport Value Forecasting," Numerical : Jurnal Matematika dan Pendidikan Matematika, vol. 7, no. 1, 2023.

W. W. S. Wei, Time Series Analysis Univeriate and Multivariate Methods Second Edition, New Jersey: Peason, 2006.

Q. Song and B. S. Chissom, "Fuzzy Time Series and its Models," Fuzzy Sets and Systems , vol. 54, pp. 269-277, 1993.

R. C. Tsaur, "A Fuzzy Time Series Markov Chain Model with an Aplicaion to Forecast The Exchange Rate Between the Taiwan an US Dollar," International Journal of Innovative Computing, Information and Control, vol. 8, no. 7, pp. 4931-4942, 2012.

D. M. ESDM, "Harga Minyak Mentah," 2018. [Online]. Available: https://migas.esdm.go.id/post/read/harga-minyak-mentah.

DOI: https://doi.org/10.13057/ijas.v6i1.79907

Refbacks

  • There are currently no refbacks.