Perbandingan Metode-metode Peramalan Statistika untuk Data Indeks Harga Pangan

Aris Gunaryati(1*), Fauziah Fauziah(2), Septi Andryana(3)

(1) Fakultas Teknologi Komunikasi dan Informatika - Universitas Nasional
(2) Fakultas Teknologi Komunikasi dan Informatika - Universitas Nasional
(3) Fakultas Teknologi Komunikasi dan Informatika - Universitas Nasional
(*) Corresponding Author

Abstract


The food issue is very important to predict the price of food, especially rice, in the future. This is because rice is the Indonesian staple food, the price of which must be always made stable and affordable for the community. Therefore, it is necessary to make a proper forecasting model to know the approximate price of rice in the future. The forecasting method that is often used in researches is a quantitative forecasting method with time series data. This research is conducted to make comparison among the statistic forecasting methods, namely trend analysis, exponential smoothing and decomposition to analyze the development of average rice price at Indonesian wholesaler level from 2010 to 2016.  The existing data shows that the most suitable forecasting model for the average data of rice price at Indonesian wholesaler level in 2010 to 2016 is Double Exponential Smoothing (Brown), with MSE level of 188,086.086. and that the prediction about average rice price in 2017 reaches Rp. 11600,- with the actual price of Rp. 11534,-

Keywords


decomposition, exponential smoothing, forecasting, MSE, trend

Full Text:

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References


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DOI: http://dx.doi.org/10.30998/string.v2i3.2200

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