Aplikasi Metode Arima Box-Jenkins Untuk Meramalkan Penggunaan Harian Data Seluler
DOI:
https://doi.org/10.31605/jomta.v2i1.749Keywords:
cellular data, ARIMA , time seriesAbstract
The Box-Jenkins method is one of the time forecasting methods series. This method uses values in the past as the dependent variable and variable independently ignored. The Box-Jenkins method has the advantage of being usable on non-stationary data can be used on all data patterns so that this method can be used to predict the daily use of cellular data. The purpose of the study to find out the model and predict the amount of cellular data daily usage using data from March 10, 2020 to May 29, 2020. Results of the analysis shows the best model for daily use of cellular data is ARIMA (0,1,2). The best model meets the test requirements, namely the parameter significance test and diagnostic checking.
References
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[2] Montgomery, Dauglas C.,dkk., Intduction to Time Series Analysis and Forecasting. Canada : Wiley-Intercience. 2008.
[3] Shumway, Robert H & David S. Stoffer., Time Series Analysis and Its Aplication With R Examples. Springer Texts in Statistic, 2016.
[4] Suhartono, Analisis Data Statistik dengan R. Surabaya : ITS. 2008.
[5] Salwa, N dkk. “Peramalan Harga Bitcoin Menggunakan Model ARIMA (Autoregressive Integrated Moving Average ) ”. Journal of Data Anaylis.Vol 1. No. 1, pp 21-31, 2018
Published
2020-08-26
Issue
Section
Articles
