Abstract
This study aims to compare the best method on the forecasting system of rainfall in Medan using Single Exponential Smoothing (SES), Naive Model, and Seasonal Autoregressive Integrated Moving Average (SARIMA) . The data used in this study is rainfall data for 10 years (2009 – 2019). From the simulation by comparing existing method, the best model is SES with and value of MAPE (Mean Absolut Percentage Error) sebesar 2,47%. And then SARIMA (1,01,1)(4,0,3)12 whit value of MAPE is2,93%. Both of this model is high accurate model because value of MAPE resulted < 10%.
Highlights
This study aims to compare the best method on the forecasting system of rainfall in Medan using Single Exponential Smoothing (SES), Naive Model, and Seasonal Autoregressive Integrated Moving Average (SARIMA)
Berdasarkan hasil penelitian [3], hasil yang diperoleh dari peramalan menggunakan metode Single Exponential Smoothing lebih tepat dibanding metode Exponential Smoothing Adjusted for Trend (Holt’s Method)
Pemodelan dan Peramalan Data Deret Waktu dengan Metode
Summary
Peramalan merupakan suatu kegiatan untuk memprediksi kejadian di masa yang akan datang dengan menggunakan dan mempertimbangkan data dari masa lampau [1]. Pola musiman merupakan fluktuasi dari data yang terjadi secara periodik dalam kurun waktu tertentu seperti harian, mingguan atau bulanan. Terdapat beberapa metode smoothing yang umum digunakan dalam peramalan time series diantaranya adalah Naive Model, Simple Average, Moving Average, Single Exponential Smoothing, Double Moving Average, Double Exponential Smoothing, Winters, dll. Berdasarkan hasil penelitian [3], hasil yang diperoleh dari peramalan menggunakan metode Single Exponential Smoothing lebih tepat dibanding metode Exponential Smoothing Adjusted for Trend (Holt’s Method). Montgomery D (1990) menerangkan bahwa exponential smoothing adalah metode yang banyak digunakan dalam analisis time series. Dalam penelitian ini akan dilakukan perbandingan hasil peramalan curah hujan di kota medan menggunakan metode SARIMA, metode Single Exponential Smoothing dan metode Naïve
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