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PERAMALAN HARGA MINYAK MENTAH INDONESIA MENGGUNAKAN ALGORITMA RANDOM FOREST

Selvi Annisa orcid  -  Program Studi Statistika, Universitas Lambung Mangkurat, Jl. A. Yani KM.35,5, Banjarbaru, Indonesia, Indonesia
*Yeni Rahkmawati orcid scopus  -  Program Studi Statistika, Universitas Lambung Mangkurat, Jl. A. Yani KM.35,5, Banjarbaru, Indonesia, Indonesia
Hardianti Hafid orcid  -  Program Studi Statistika, Universitas Negeri Makassar, Jln. Daeng Tata, Makassar, 90224, Indonesia, Indonesia
Open Access Copyright 2024 Jurnal Gaussian under http://creativecommons.org/licenses/by-nc-sa/4.0.

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Abstract

Crude oil prices are a critical global macroeconomic indicator, influencing central bank policies, investment strategies, and the pricing of oil-dependent goods. Accurate forecasting of crude oil prices is essential for informed decision-making in these areas. This study aims to forecast the price of Indonesian crude oil from April 2024 to December 2024 using the Random Forest algorithm. A quantitative approach utilizes monthly data on Indonesian crude oil prices from August 2017 to March 2024. The forecasting performance is evaluated using the Mean Absolute Percentage Error (MAPE). The findings indicate that the Random Forest model, with Lag 1 as the input variable, produces forecasts with a MAPE of 6.215%, categorizing it as excellent. The projected price range for Indonesian crude oil from April to December 2024 is between 70 and 87 USD per barrel. This forecast suggests potential price fluctuations driven by geopolitical conflicts in Europe and the Middle East, global demand for crude oil, and varying economic growth rates.

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Keywords: Machine learning; Time series; Random Forest; Crude oil

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