Analisis Komparatif ARIMA dan Prophet dengan Studi Kasus Dataset Pendaftaran Mahasiswa Baru - Cato Chandra; Setia Budi (Jurnal Teknik Informatika dan Sistem Informasi, 2020)
This research presents all studies, methodologies, and results about testing the accuracy of predictions on new student marketing data by region using the Prophet and Autoregressive Integrated Moving Average (ARIMA) methods. The dataset selected for this study uses 26 years of actual data that has an annual interval. The data was prepared for time series forecasting analysis, therefore, several numbers of data preprocessing were applied such as log transformation and resampling. To get efficient variables, the best variables will be sought to improve the accuracy of predictions. Both models will conduct training and test data to produce values that can be compared using the metric regression model. Based on the training conducted, Prophet has better performance than ARIMA.