Perbandingan Model Time Series Pada Peramalan Inflasi Di Kota Batam
Kata Kunci:
Inflation, Time Series, Seasonal Models, Additive ModelsAbstrak
Inflation is a problem that disrupts the economy of every country, as well as developing countries such as Indonesia which is an agricultural country. To maintain the instability of the inflation rate, an alternative way that can be done is to forecast time series data. This study aims to predict the value of inflation that will occur in Batam City in the future so that this research is useful for taking appropriate action can be done. Seasonal time series analysis which is a forecasting method based on synthesis of historical data patterns. For data analysis, the author chose the help of Minitab software. The data used is secondary data in the form of monthly time series data, namely inflation rate data for Batam city from January 2014 to July 2022. Based on the results of the analysis, comparison of MSE values between SMA models, Multiplicativ and Additive, the best model is the Additive model, so that the model is what we use in forecasting
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