Penerapan Model Arima untuk Memproyeksi Tren Harga TBS Sawit di Provinsi Jambi
DOI:
https://doi.org/10.37481/sjr.v8i1.1040Keywords:
ARIMA, Forecasting, Oil Palm FFB, Price, StataAbstract
The palm oil industry in Indonesia, especially in Jambi Province, plays an important role in the economy, contributing to GDP, employment, and exports in Indonesia. However, farmers and industry players face challenges in the form of fluctuations in palm oil FFB prices, which are influenced by domestic factors such as government policies and weather, as well as external factors such as global market demand for CPO and renewable energy policies. Therefore, research into projecting future palm oil FFB prices is needed as a reference in determining strategies for farmers and palm oil business actors, including policy makers. One way to predict these prices is to use a statistical model that identifies price movement patterns based on historical data, namely the ARIMA model. Thus, the objectives of this study are (1) to estimate the optimal ARIMA model based on the characteristics of the available price data, and (2) to identify projections of future price trends by applying the ARIMA model. The price data used is weekly price data for the period 2019-2024. Several validity tests such as the Unit Root and White Noise tests are used in the ARIMA model estimation process. The ARIMA (1,1,1) model was selected as the most optimal and effective model for projecting the price of Palm Oil Fruit Bunches for 52 weeks in 2025, where the trend shows a positive direction.
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