Peramalan Harga Minyak Mentah Indonesia dengan Model Hibrida ARIMA–FTS Cheng


Authors

  • Erin Jihan Wahyu Kusuma Universitas Sebelas Maret, Surakarta, Indonesia
  • Etik Zukhronah Universitas Sebelas Maret, Surakarta, Indonesia
  • Yuliana Susanti Universitas Sebelas Maret, Surakarta, Indonesia

DOI:

https://doi.org/10.47065/jimat.v5i3.629

Keywords:

Forecasting; Crude Price Oil; Hybrid; ARIMA; FTS Cheng; MAPE

Abstract

Economic growth is a key indicator of successful economic activities, with adequate crude oil availability playing a crucial role in supporting a country's economic development. This study aims to forecast Indonesian crude oil prices using an Autoregressive Integrated Moving Average (ARIMA)–Fuzzy Time Series (FTS) Cheng hybrid model. The data utilized consists of monthly Indonesian crude oil prices from January 2013 to April 2023 for training and from May 2023 to December 2024 for testing. The training data is modeled using ARIMA, and the residuals from the ARIMA model are subsequently analyzed using the FTS Cheng approach. The hybrid ARIMA-FTS Cheng forecast is generated by combining the predictions from both the ARIMA and FTS Cheng models. The results of the study show that the hybrid ARIMA–FTS Cheng model produced an MAPE of 7.46% on the training data and 4.57% on the testing data. Therefore, the ARIMA–FTS Cheng hybrid model is considered suitable for forecasting Indonesia's crude oil prices.

Downloads

Download data is not yet available.

References

esdm.go.id, “ICP November 2014 Turun U$ 8,33 per Barel,” www.esdm.go.id. Diakses: 22 Januari 2025. [Daring]. Tersedia pada: https://www.esdm.go.id/id/media-center/arsip-berita/icp-november-2014-turun-u-833-per-barel

esdm.go.id, “ICP Desember 2016 Naik Jadi US$ 51,09 per Barel,” www.esdm.go.id. Diakses: 22 Januari 2025. [Daring]. Tersedia pada: https://migas.esdm.go.id/post/icp-desember-2016-naik-jadi-us$-51,09-per-barel

esdm.go.id, “Pertumbuhan Ekonomi Global Melemah, ICP November 2018 Turun Lagi Jadi US$ 62,98 per Barel,” www.esdm.go.id. Diakses: 22 Januari 2025. [Daring]. Tersedia pada: https://www.esdm.go.id/id/berita-unit/direktorat-jenderal-minyak-dan-gas-bumi/pertumbuhan-ekonomi-global-melemah-icp-november-2018-turun-lagi-jadi-us-6298-per-barel

esdm.go.id, “Covid-19 Meluas dan Lockdown Negara Konsumen Minyak, ICP Maret 2020 Tertekan Lagi Jadi US$ 34,23 per Barel,” www.esdm.go.id. Diakses: 22 Januari 2025. [Daring]. Tersedia pada: https://migas.esdm.go.id/post/covid-19-meluas-dan-lockdown-negara-konsumen-minyak-icp-maret-2020-tertekan-lagi-jadi-us-34-23-per-barel

W. W. S. Wei, Time Series Analysis: Univariate and Multivariate Methods. Pearson Education, 2006.

Q. Song dan B. S. Chissom, “Forecasting enrollments with fuzzy time series - Part I,” Fuzzy Sets Syst., vol. 54, no. 1, hal. 1–9, 1993, doi: 10.1016/0165- 0114(93)90355-L.

G. P. Zhang, “Time series forecasting using a hybrid ARIMA and neural network model,” Neurocomputing, vol. 50, hal. 159–175, 2003, doi: 10.1016/S0925-2312(01)00702-0.

A. Tunggal dan R. Prathivi, “Analisis Perbandingan Metode Arima Dan LSTM Untuk Prediksi Penjualan Harga Saham BNI,” Kesatria J. Penerapan Sist. Inf. (Komputer dan Manajemen), vol. 6, no. 1, hal. 158–164, 2025.

D. Fakhriyana dan I. I. Brilliant, “Penerapan Metode Fuzzy Time Series (FTS) Cheng dan Markov-Chain untuk Peramalan Indonesia Crude Oil Price (ICP),” Indones. J. Appl. Stat., vol. 6, no. 1, hal. 44–56, 2023, doi: 10.13057/ijas.v6i1.79907.

D. K. Sari dan A. Sa’adah, “Perbandingan Fuzzy Time Series Chen dan Cheng untuk Peramalan Harga Beras di Kabupaten Banyumas,” Euler J. Ilm. Mat. Sains dan Teknol., vol. 12, no. 2, hal. 170–174, 2024.

J. Bidin, N. Sharif, S. F. S. Abas, K. A. K. Akil, dan N. A. Abdullah, “Cheng Fuzzy Time Series Model to Forecast the Price of Crude Oil in Malaysia,” J. Comput. Res. Innov., vol. 7, no. 2, hal. 196–210, 2022, doi: 10.24191/jcrinn.v7i2.304.

I. N. G. Neyun, W. Sulandari, dan I. Slamet, “Hibrida Autoregresiive Integrated Moving Average dan Fuzzy Time Series Cheng untuk Prediksi Harga Saham Autoregresiive Integrated Moving Average and Fuzzy Time Series Cheng Hybrid for Predicting Stock Price,” J. Bumigora Inf. Technol., vol. 5, no. 2, hal. 139–150, 2023.

U. S. Mayanti, O. Darnius, dan I. Sitepu, “Model Hibrida Autoregressive Integrated Moving Average (ARIMA) Dan Fuzzy Time Series (FTS) Untuk Peramalan Produksi Kelapa Sawit PT .Perkebunan Nusantara II,” Cart. J. Pendidik. Mat., vol. 6, no. 1, hal. 33–40, 2023.

D. C. Montgomery, C. L. Jennings, dan M. Kulahci, Introduction to Time Series Analysis and Forecasting. New Jersey: John Wiley & Sons. Inc., 2008.

Nuryadi, T. D. Astuti, E. S. Utami, dan M. Budiantara, Dasar-dasar Statistik Penelitian. 2017.

C. H. Cheng, T. L. Chen, H. J. Teoh, dan C. H. Chiang, “Fuzzy time-series based on adaptive expectation model for TAIEX forecasting,” Expert Syst. Appl., vol. 34, no. 2, hal. 1126–1132, 2008.

K. Huarng, “Effective lengths of intervals to improve forecasting in fuzzy time series,” Fuzzy Sets Syst., vol. 123, no. 3, hal. 387–394, 2001.

W. Sulandari, Suhartono, dan Y. Yudhanto, Aplikasi Fuzzy Pada Pemodelan Runtun Waktu. 2020.

S. M. Chen, “Forecasting enrollments based on fuzzy time series,” Fuzzy Sets Syst., vol. 81, no. 3, hal. 311–319, 1996, doi: 10.1016/0165-0114(95)00220-0.

J. E. Hanke dan D. Wichern, Business Forecasting, Ninth. Pearson Education Limited, 2014.

P. C. Chang, Y. W. Wang, dan C. H. Liu, “The development of a weighted evolving fuzzy neural network for PCB sales forecasting,” Expert Syst. Appl., vol. 32, no. 1, hal. 86–96, 2007.


Bila bermanfaat silahkan share artikel ini

Berikan Komentar Anda terhadap artikel Peramalan Harga Minyak Mentah Indonesia dengan Model Hibrida ARIMA–FTS Cheng

Dimensions Badge

ARTICLE HISTORY

Published: 2025-07-21

Abstract View: 58 times
PDF Download: 37 times

Issue

Section

Articles