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Sales Forecasting Double Moving Average and Double Exponential Smoothing Indihome PematangSiantar 2018-2021 Using python

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Forecast DES.png
Forecast DES.png
 
 
Forecast DMA.png
Forecast DMA.png
 
 
Forecast_DMA_DES_Sales.ipynb
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README.md
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data penjualan indihome.xlsx
data penjualan indihome.xlsx
 
 

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Double Moving Average (DMA) and Double Exponential Smoothing

Dataset = Sales Report Indihome PematangSiantar

Times = January 2018 until December 2021

  • Double Moving Average is best models for historical data with a trend but no seasonality.

  • Double Eksponensial Smoothing is best models for data have a trend and do not have a seasonal component.

  • DMA and DES are suitable for short-term forecasting

  • Exploratory Data Analysis by monthly, analysis and forecasting are carried out by comparing MAPE

  • Summary = MAPE DMA < MAPE DES with optimal parameter

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Sales Forecasting Double Moving Average and Double Exponential Smoothing Indihome PematangSiantar 2018-2021 Using python

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python sales machine-learning exploratory-data-analysis forecasting des dma time-series-analysis time-series-forecasting indihome double-exponential-smoothing double-moving-average

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