Prediksi jumlah pengunjung webstie resmi Kabupaten Malang menggunakan metode autoregresive integreted moving average
Keywords:
Arima, time series, website, stasioner, parameterAbstract
This study aims to predict the number of visitors to the official website using the ARIMA (Autoregressive Integrated Moving Average) method. Visitors to the official website are an important indicator in measuring the level of interaction and public interest in the information provided by local governments. In order to improve forecasting accuracy, the first step is to analyze visitor historical data to identify patterns and trends that may exist. Next, testing the stationarity of the data using ACF (Autocorrelation Function) and PACF (Partial Autocorrelation Function) to determine the correct forecasting steps. From the results of the analysis, it was found that the official website visitor data does not have a stationary nature, so it is necessary to do differencing to get stationary data in order to build the ARIMA model. After that, the next step is to determine the most suitable ARIMA model parameters by analyzing the ACF and PACF values from the differentiated data. With the specified model parameters, the validity of the ARIMA model is tested using actual visitor data.
Downloads
Downloads
Published
How to Cite
Issue
Section
License
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work’s authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal’s published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
