Analisa Perbandingan Metode SARIMAX dan Prophet Dalam Prediksi Kebutuhan Beras - Aditya, Fadhila; Safrizal, Safrizal (Forum Kerjasama Pendidikan Tinggi (FKPT), 2025)
Accurate forecasting of rice demand is essential to maintain the balance between supply and consumption at the regional level. However, seasonal fluctuations and dynamic population growth often cause mismatches between rice availability and demand. This study addresses these issues by comparing two time-series forecasting methods, the Seasonal Autoregressive Integrated Moving Average with Exogenous Variables (SARIMAX) and Prophet, in predicting rice demand in Central Java Province, Indonesia. The comparison was conducted because SARIMAX effectively explains the influence of exogenous variables such as population, while Prophet offers greater flexibility in capturing nonlinear trends and seasonal patterns. The study used secondary data from the Central Bureau of Statistics (BPS) covering the period from January 2021 to December 2023. Model accuracy was evaluated using MAE, RMSE, MAPE, and sMAPE metrics. The results show that Prophet achieved a MAPE of 4.72%, outperforming SARIMAX at 5.49%, categorized as “highly accurate.” Prophet was more adaptive to short-term variations, whereas SARIMAX provided stronger interpretability of causal factors.