Forecasting Kandaga Library Visitors Using Autoregressive Integrated Moving Average (ARIMA) Model - Ramadhan, Ndaru; Wahyu Ramadhani, Ima Azzahra; Wulandari, Oktafiana Retno (Universitas Islam Indonesia, 2024)
College libraries must provide optimal library services, which requires careful planning. The fluctuating number of visitors means that libraries must make preventive efforts to provide excellent service in the future, one of which is forecasting the number of visitors. Forecasting the number of visitors can help libraries prepare for surges in the number of visitors. This research aims to forecast the number of visitors at the Kandaga Library using the ARIMA model as a preventive effort for the Kandaga Library to provide better library services and improve service quality and user satisfaction. This research uses descriptive quantitative methods through the ARIMA forecasting model assisted by SPSS Version 26 software. The best ARIMA model used is the ARIMA model (4,0,12), with a MAPE value of 26.89%. Based on the results of the ARIMA forecasting model (4,0,12), the predicted total number of visitors at the Kandaga Library from October 2024 to October 2025 is 105,742 visitors. Compared with Exper Modeler, which has a MAPE value of 13.10%, the ARIMA model (4,0,12) is no more accurate for forecasting the number of visitors. Therefore, it is essential for further research to compare various forecasting models to obtain the most appropriate and precise model for predicting the number of visitors.