Analisa Dan Implementasi Data Mining Untuk Memprediksi Jumlah Material Bangunan Menggunakan Algoritma Autoreggresive Intergrated Moving Average (ARIMA)
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Ester Mangisi Tumanggor
*
Universitas Budi Darma, Medan,
Indonesia
(*) Corresponding Author
Abstract
Prediction (Forecasting) is done by almost everyone, be it the government, businessmen, or ordinary people. Forecasted problems also vary, such as forecasted rainfall, possible winners in the presidential election, game scores, sales numbers or inflation rates. The ARIMA method is one method that can be used to overcome something related to series and forecasting situations. It should be understood that ARIMA is very good at forecasting. ARIMA is a method developed by Box-Jenkins which is a combination of projection method, regression method and decomposition method. The ARIMA method only uses one variable as the basis for making predictions so that in this model there is no independent variable term used to predict the value of the dependent variable. This model uses values in the past and present as a basis for prediction. Therefore, it is very appropriate to use in predicting
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References
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Pages: 373-377
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