Analisis Komparatif ARIMA dan Prophet dengan Studi Kasus Dataset Pendaftaran Mahasiswa Baru
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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.
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How to Cite
C. Chandra and S. Budi, “Analisis Komparatif ARIMA dan Prophet dengan Studi Kasus Dataset Pendaftaran Mahasiswa Baru”, JuTISI, vol. 6, no. 2, Aug. 2020.
This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial used, distribution and reproduction in any medium.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.