Evaluating the Impact of the Government Floor Price Policy (HPP) on Farm-Gate-Level Harvested Dry Paddy (GKP) Price Trends Through Machine Learning-Based Forecasting

Government Purchasing Price (Harga Pembelian Pemerintah, HPP) is a policy established to maintain stable Harvested Dry Paddy (Gabah Kering Panen, GKP) prices at the farm-gate level and to protect farmers from declining incomes due to price drops during harvest periods. The effectiveness of the policy has yet to be evaluated; however, reports indicate that paddy prices in several regions are still below the HPP rate. This study explores variations in the trends and volatility of farm-gate-level GKP prices before and after the adoption of the new HPP policy and constructs a provincial-level forecasting model based on the Extreme Gradient Boosting (XGBoost) methodology using a daily provincial panel dataset covering the period from 1 January 2023 to 31 December 2025. An analysis of six sample provinces was performed: the Special Region of Yogyakarta (DIY), East Java, South Kalimantan, Bali, West Sumatra, and Jambi. The model was trained using pre-policy observations and recursively forecasted post-policy prices under a hypothetical no-HPP-policy scenario, which were then descriptively compared with observed prices after the policy was implemented. The results show that the model delivers very high prediction accuracy, with tested Mean Absolute Percentage Error (MAPE) values ranging from 0.61% to 1.60% and Root Mean Squared Error (RMSE) values ranging from IDR 50.31 to IDR 158.04. The comparison shows that observed post-policy GKP prices tend to remain higher and more stable over time than those forecasted under the no-HPP-policy scenario, although the magnitude of this difference varies among regions. These findings provide descriptive forecasting evidence regarding post-policy GKP price dynamics rather than definitive causal estimates of policy impact.