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Journal : Jurnal Teknik Komputer AMIK BSI

Application of Prediction Models Based on Moving Average, Exponential Smoothing and Trend Analysis on Indonesian Palm Oil Exports Baidawi, Taufik; Effendi, Muhammad Ridwan; Kuswara, Heri; Wardah, Siti; Falgenti, Kursehi
JURNAL TEKNIK KOMPUTER AMIK BSI Vol 11, No 1 (2025): Periode Januari 2025
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/jtk.v11i1.25194

Abstract

Palm oil is a strategic commodity for Indonesia, significantly contributing to state revenue and foreign exchange. In 2022, its export value reached USD 33.7 billion. Accurate forecasting of palm oil exports is crucial due to fluctuating market conditions influenced by global demand, prices, and government policies. However, existing studies on forecasting Indonesian palm oil exports are limited, with most research focusing on other agricultural commodities. This study applies Moving Average, Exponential Smoothing, and Trend Analysis methods to forecast palm oil exports and determine the most accurate method. The results show that the Trend Analysis method yields the lowest Mean Absolute Deviation (MAD = 18505.67) and Mean Squared Error (MSE = 436747200), indicating superior accuracy compared to the other methods. The findings suggest that Trend Analysis can provide stakeholders government, companies, and farmers with valuable insights for strategic decision-making. This research contributes to the development of more precise forecasting models, supporting Indonesia's palm oil industry in maintaining its global competitiveness.