Peramalan Volume Timbulan Sampah dengan Memanfaatkan Indeks Google Trends Menggunakan Metode SARIMAX - Hidayat, Anang Kurnia; Wijayanto, Arie Wahyu (Politeknik Statistika STIS, 2025)
In recent years, the Special Region of Yogyakarta has faced a growing challenge of waste generation exceeding its management capacity. This situation underscores the urgency of developing a long-term, data-driven waste management strategy. This study aims to build an accurate forecasting model for waste volume using real-time data from the Google Trends Index (GTI) alongside official statistical data as exogenous variables. The forecasting methods employed are SARIMA and SARIMAX, tested with various parameter and variable combinations. The best-performing model is SARIMAX(1,1,1)(1,0,0)12 with the Production Index (IBS) and the GTI for the keyword “sampah” (waste) as exogenous variables, achieving a MAPE of 5.7873 (classified as very good) and an RMSE of 46.7509. The forecast shows an upward trend in mid-2024, a decline at the end of 2024, and a sharp increase in early 2025. These results can inform adaptive waste management policies, particularly in strengthening upstream strategies such as waste reduction, sorting, and recycling.