Forecasting The Highest Number Of Hotel Visitors In Mojokerto Regency Using Arima Model

Gading Putri Diniarti; Rizka Hadiwiyanti; Prasasti Karunia F. A

doi:10.34288/jri.v7i4.388

Authors

Gading Putri Diniarti Universitas Pembangunan Nasional "Veteran" Jawa Timur
Rizka Hadiwiyanti
Prasasti Karunia F. A

(*) Corresponding Author

DOI:

https://doi.org/10.34288/jri.v7i4.388

Keywords:

time series forecasting, hotel visitor prediction, MSE, RMSE, MAPE, auto ARIMA

Abstract

This study aims to forecast the number of hotel visitors in Mojokerto Regency using the Autoregressive Integrated Moving Average (ARIMA) model based on monthly data from 2022 to 2024 provided by the Department of Culture, Youth, Sports, and Tourism (Disbudporapar). The research focuses on three hotels with the highest number of visitors: Hotel Grand Whiz, Puri Indah Hotel, and Hotel Arrayana. The implementation was carried out using Python via the Google Colab platform, involving several analytical stages including data stationarity testing (ADF), differencing, identification of ARIMA parameters (p, d, q) using ACF and PACF plots, automatic model estimation with auto ARIMA, and residual diagnostics. Model performance was evaluated using MSE, RMSE, and MAPE. The results show that ARIMA performed best on Puri Indah Hotel data with a MAPE of 9.65%, indicating high accuracy, while performance was lowest for Hotel Arrayana with a MAPE of 32.31%. Visualization of the predictions revealed that ARIMA works effectively for stable patterns but is less adaptive to volatile trends. The implementation of ARIMA proves to be a useful tool in supporting data-driven decision-making for tourism planning and hotel operational strategy in Mojokerto Regency

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