Kajian Model Chen dan Model Lee pada Metode Fuzzy Time Series serta Peramalan pada Produksi Crude Palm Oil (CPO)

Abstract

This study aims to examine two forecasting models, namely the Chen model and the Lee model, applied to the Fuzzy Time Series method in predicting the production of crude palm oil (CPO) in Riau Province. The data used is secondary data on CPO production from the Central Bureau of Statistics (BPS) of Riau Province between 2018 and 2022. The Chen and Lee models are implemented to predict production values, and the forecast results are compared using the Mean Absolute Percentage Error (MAPE) as an accuracy measure. The results of the study indicate that both models are capable of forecasting CPO production with different levels of accuracy. For the predicted result in January 2023, the FTS Chen model forecasts 795,061.5 tons with an accuracy of MAPE 6.316%, while the FTS Lee model forecasts 748,307.4 tons with an accuracy of MAPE 5.195%. The Lee model demonstrated better predictive accuracy than the Chen Model, as indicated by the lower MAPE value. This study is expected to assist relevant parties in planning future CPO production.