Kestabilan harga beras merupakan faktor penting bagi masyarakat Indonesia karena beras menjadi komoditas utama dalam pemenuhan kebutuhan pangan sehari-hari. Namun, fluktuasi harga beras sering menimbulkan ketidakpastian dan memengaruhi daya beli masyarakat. Penelitian ini bertujuan memprediksi fluktuasi harga beras dengan algoritma Random Forest serta menyajikan hasilnya melalui Graphical User Interface (GUI) agar masyarakat dapat mengakses informasi prediksi dengan mudah. Data harga beras 34 provinsi periode 2021 2024 dibagi menjadi 80% training dan 20% testing. Evaluasi menggunakan MAE, RMSE, R², MAPE, dan confusion matrix. Hasil menunjukkan performa baik pada tiga provinsi: Jawa Barat (MAE 47,35, RMSE 125,57, R² 0,9774, MAPE 0,40%, akurasi 0,94), Jawa Tengah (MAE 56,35, RMSE 149,03, R² 0,9763, MAPE 0,49%, akurasi 0,97), dan Jawa Timur (MAE 56,38, RMSE 160,28, R² 0,9769, MAPE 0,51%, akurasi 1,00). GUI yang dibangun memudahkan masyarakat mengakses dan memahami prediksi harga beras untuk perencanaan konsumsi dan antisipasi perubahan harga.

Rice price stability is an essential factor for Indonesian society since rice is the main commodity for fulfilling daily food needs. However, fluctuations in rice prices often create uncertainty and affect people’s purchasing power. This study aims to predict rice price fluctuations using the Random Forest algorithm and present the results through a Graphical User Interface (GUI) so that the public can easily access prediction information. Rice price data from 34 provinces in Indonesia for the period 2021–2024 was divided into 80% training and 20% testing. The evaluation employed MAE, RMSE, R², MAPE, and confusion matrix. The results show good performance in three provinces: West Java (MAE 47.35, RMSE 125.57, R² 0.9774, MAPE 0.40%, accuracy 0.94), Central Java (MAE 56.35, RMSE 149.03, R² 0.9763, MAPE 0.49%, accuracy 0.97), and East Java (MAE 56.38, RMSE 160.28, R² 0.9769, MAPE 0.51%, accuracy 1.00). The developed GUI helps the public access and understand rice price predictions for consumption planning and anticipating price fluctuations.