Forecasting the Number of Visitors to Rahmat Museum And Gallery Using the Seasonal Autoregressive Integrated Moving Average with Exogenous Variables (SARIMAX) Model - tajrin, tajrin tajrin; Wintania, Evelyn; Purba, Musa Ferdianshah; Kholik, Fatimatuzzahro (International Journal of Artificial Intelligence Research, 2025)
Fluctuations in monthly visitor numbers present challenges for tourism management in planning operational and promotional strategies. Rahmat International Wildlife Museum & Gallery, a leading educational tourism destination in Medan, experiences dynamic variations in visitor numbers influenced by seasonal patterns and external conditions. This study aims to forecast monthly visitor numbers using the SARIMAX model. Monthly visitor data from January 2021 to November 2025 were analyzed, incorporating national holidays and the COVID-19 period as external variables. The modeling process included data preprocessing, stationarity testing using the Augmented Dickey-Fuller (ADF) test, parameter identification through ACF and PACF analysis, and model evaluation using RMSE and MAPE metrics. The results indicate that the SARIMA(1,0,1) model without exogenous variables provides the best predictive performance. Forecasting for the next 12 months suggests relatively stable visitor numbers, ranging from approximately 1,800 at the beginning of the forecast period to around 1,500 toward the end, indicating a gradual declining trend. These findings provide a data-driven foundation for strategic planning and visitor management at the museum