Peramalan Harga Emas Berjangka Menggunakan Metode ARIMA-GARCH

Mauizatun Hasanah, Mega Ramatika Putri, Khairil Anwar Notodiputro, Yenni Angraini, Laily Nissa Atul Mualifah

Abstract


Gold futures price forecasting plays an important role in investment decision-making and risk management, especially in the midst of volatile commodity market dynamics. This research aims to build an accurate gold futures price forecasting model by combining Autoregressive Integrated Moving Average (ARIMA) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models. The ARIMA model is used to capture linear patterns and historical trends in time series data, while the GARCH model is able to handle the high volatility characteristic of gold price movements, something that conventional forecasting models often fail to capture. The data used in this study is daily gold futures price data collected over the period January 3, 2023 to March 31, 2025, which covers both normal market conditions and periods of turmoil, making it relevant to describe the overall market dynamics. The forecasting results show that the ARIMA-GARCH model with components (3,1,3) (1,1) with a MAPE of 4.52% indicates a good level of accuracy in the context of forecasting gold futures prices that have high volatility. Thus, this model provides precise forecasting results with actual data so that it can be used by market participants and policy makers in managing risks and designing strategies.

Keywords


Forecasting; ARIMA-GARCH; Gold Futures

Full Text:

PDF

References


F. S. Saputra, “Prediksi Harga Emas di Masa Depan,” 2024. [Online]. Available: https://blog.indogold.id/prediksi-harga-emas-di-masa-depan/. [Accessed: 31-Jul-2025].

T. Reuters, “Gold eyes $2,000 mark in speedy record-breaking run,” 2024. [Online]. Available: https://www.weforum.org/stories/2020/07/gold-price-covid19-fiscal-policy-response/. [Accessed: 31-Jul-2025].

Effendi and L. Monica, “Dolar AS melemah, harga emas menguat tipis. Cermati arah The Fed?,” 2025. [Online]. Available: https://www.idnfinancials.com/id/news/54274/dolar-as-melemah-harga-emas-menguat-tipis-cermati-arah-the-fed. [Accessed: 31-Jul-2025].

R. J. Hyndman and G. Athanasopoulos, Forecasting: Principles and Practice, 3rd ed. Melbourne, Australia: OTexts, 2021.

G. Aye, R. Gupta, S. Hammoudeh, and W. J. Kim, “Forecasting the price of gold using dynamic model averaging,” Int. Rev. Financ. Anal., vol. 41, pp. 257–266, Oct. 2015, doi: 10.1016/j.irfa.2015.03.010.

R. Nargunam, W. W. S. Wei, and N. Anuradha, “Investigating seasonality, policy intervention and forecasting in the Indian gold futures market: a comparison based on modeling non-constant variance using two different methods,” Financ. Innov., vol. 7, no. 1, p. 62, Dec. 2021, doi: 10.1186/s40854-021-00283-9.

S. Setyowibowo, M. As’ad, S. Sujito, and E. Farida, “Forecasting of Daily Gold Price using ARIMA-GARCH Hybrid Model,” J. Ekon. Pembang., vol. 19, no. 2, pp. 257–270, Feb. 2022, doi: 10.29259/jep.v19i2.13903.

I. F. Amri, S. A. Astuti, I. Sulistiya, A. Suherdi, and M. A. Haris, “Peramalan Harga Emas Antam Menggunakan Metode Generalized Autoregressive Conditional Heterokedasticity (GARCH),” Unisda J. Math. Comput. Sci. UJMC, vol. 10, no. 1, pp. 26–35, June 2024, doi: 10.52166/ujmc.v10i1.4679.

H. R. Sari, S. Wahyuningsih, and M. Siringoringo, “Indonesia Gold Price Forecasting Using ARIMA Model (0,1,1) - GARCH (1,0),” Eksponensial, vol. 15, no. 1, p. 1, 2024, doi: 10.30872/eksponensial.v15i1.1265.

F. A. F. Beeg, M. S. Paendong, and M. L. Mananohas, “Penerapan Model ARIMA-GARCH untuk Peramalan Harga Emas Dunia,” d’Cartesian, vol. 13, no. 2, pp. 73–79, Oct. 2024, doi: 10.35799/dc.13.2.2024.55551.

R. Paswan, “Gold prices edge higher with focus on Fed’s policy decision,” 2024. [Online]. Available: https://www.livemint.com/market/commodities/gold-prices-edge-higher-with-focus-on-fed-s-policy-decision-11734492519175.html. [Accessed: 15-Jul-2025].

Reuters, “Gold shines on rising US Fed rate-cut outlook,” 2024. [Online]. Available: https://www.cnbctv18.com/market/commodities/gold-shines-on-rising-us-fed-rate-cut-outlook-19444796.htm. [Accessed: 15-Jul-2025].

R. Jaiswal and R. Uchil, “An Analysis of Gold Futures as an Alternative Asset: Evidence from India,” Int. J. Econ. Financ., vol. 8, no. 6, pp. 144–150, 2018, doi: 10.32479/ijefi.7346.

I. W. Misshuari, E. Kurniyaningrum, and R. Saily, “Application of Arima Method for Rainfall Forecasting in Asahan Region,” Indones. J. Constr. Eng. Sustain. Dev. Cesd, vol. 6, no. 2, pp. 22–28, 2023, doi: 10.25105/cesd.v6i2.18815.

G. E. P. Box, G. M. Jenkins, G. C. Reinsel, and G. M. Ljung, No TitleTime Series Analysis: Forecasting and Control, 5th ed. Wiley, 2016.

M. S. Wabomba, “Modeling and Forecasting Kenyan GDP Using Autoregressive Integrated Moving Average (ARIMA) Models,” Sci. J. Appl. Math. Stat., vol. 4, no. 2, p. 64, 2016, doi: 10.11648/j.sjams.20160402.18.

A. K. Sahai, N. Rath, V. Sood, and M. P. Singh, “ARIMA modelling & forecasting of COVID-19 in top five affected countries,” Diabetes Metab. Syndr. Clin. Res. Rev., vol. 14, no. 5, pp. 1419–1427, 2020, doi: 10.1016/j.dsx.2020.07.042.

G. T. Meilania, A. V. Septiani, E. Erianti, K. A. Notodiputro, and Y. Angraini, “Pemodelan ARIMA-GARCH dalam Peramalan Kurs Rupiah Terhadap Yen dengan Masalah Keheterogenan Ragam,” Ekon. J. Econ. Bus., vol. 8, no. 1, p. 165, 2024, doi: 10.33087/ekonomis.v8i1.1294.

K. A. Notodiputro, Y. Anggraini, and L. N. A. Mualifah, Analisis Deret Waktu dengan Python: Pendekatan Box-Jenkins dan Machine Learning. IPB Press, 2025.

N. S. Maharani et al., “Aplikasi Model Arima Garch Dalam Peramalan Data Nilai Tukar Rupiah Terhadap Dolar Tahun 2017-2022,” J. Mat. Sains Dan Teknol., vol. 24, no. 1, pp. 37–50, 2023, doi: 10.33830/jmst.v24i1.4875.2023.

J. Antika, A. Mugayat, and M. Sukartini, “Analisis Volatilitas Saham Dengan Metode Arch-Garch Pada Bank Rakyat Indonesia Tahun 2019-2022,” J. Ilmu Ekon., vol. 4, no. 1, pp. 323–341, 2025, doi: 10.59827/jie.v4i1.227




DOI: https://doi.org/10.37905/euler.v13i2.32723

Refbacks

  • There are currently no refbacks.


Copyright (c) 2025 Mauizatun Hasanah, Mega Ramatika Putri, Khairil Anwar Notodiputro, Yenni Angraini, Laily Nissa Atul Mualifah

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.


Euler: Jurnal Ilmiah Matematika, Sains dan Teknologi is indexed, registered, or discoverable through:

SINTA Google Scholar GARUDA Indonesia OneSearch BASE WorldCat ROAD Dimensions

EDITORIAL OFFICE OF EULER: JURNAL ILMIAH MATEMATIKA, SAINS DAN TEKNOLOGI
AddressDepartment of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Negeri Gorontalo
Jl. Prof. Dr. Ing. B. J. Habibie, Tilongkabila, Kabupaten Bone Bolango, Gorontalo 96554, Indonesia
EmailEmail: [email protected]
WhatsApp+62 87777-586462 (WhatsApp Only)
Creative Commons CC BY-NC 4.0 Euler: Jurnal Ilmiah Matematika, Sains dan Teknologi p-ISSN: 2087-9393 | e-ISSN: 2776-3706 Published by Department of Mathematics , Universitas Negeri Gorontalo, Indonesia.

Article Copyright: Copyright in individual published articles is retained by the respective authors. Authors grant Euler the non-exclusive right of first publication.

Article License: All published articles are distributed under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0) . This license permits sharing and adaptation for noncommercial purposes with appropriate attribution.

Website Copyright: Copyright notices applying to the journal website or its administrative content are separate from the copyright and licensing terms of individual published articles.

For further information, please refer to the Copyright Notice and Open Access Policy . Powered by Public Knowledge Project OJS .