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DERET WAKTU

agamvik Dec 11th, 2019 95 Never
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  1. library(tseries)
  2. library(forecast)
  3.  
  4. Data = DATA_EMONEY
  5. #tsData = ts(as.numeric(Data$Jumlah), start=c(2009, 1), end=c(2019,10), frequency=12)
  6. tsData = ts(as.numeric(Data$Jumlah), start=c(2009, 1), end=c(2019,10), frequency=12)
  7. summary(tsData)
  8. boxplot(tsData)
  9. t.test(tsData, conf.level = 0.95)
  10. sd(tsData)
  11. var(tsData)
  12. ts.plot(tsData, ylab='Jumlah Transaksi (satuan Transaksi)', xlab='Waktu (Bulan)', main='Jumlah Transaksi Uang Elektronik di Indonesia')
  13. #par(new=TRUE)
  14. #ts.plot(tsData)
  15. adf.test(tsData)
  16. tsDatadiff = diff(tsData, difference = 50)
  17. ts.plot(tsDatadiff,ylab='Jumlah Transaksi (satuan Transaksi)', xlab='Waktu (Bulan)',main='Differensiasi 1 Jumlah Transaksi Uang Elektronik di Indonesia')
  18. adf.test(tsDatadiff)
  19. model = arima(tsData, order = c(4,2,3))
  20. model
  21. arima(tsData, order = c(4,2,3))
  22. model = arima(tsData, order = c(6,4,2))
  23. #arima(tsData, order = c(3, 50, 0))
  24.  
  25. modelauto = auto.arima(tsData)
  26.  
  27. acf(tsDatadiff, main='Plot ACF Data Differensiasi 2')
  28. pacf(tsDatadiff, main='Plot PACF Data Differensiasi 2')
  29.  
  30. fcast = forecast(modelauto, h = 14, level = 0.95)
  31. plot(fcast)
  32.  
  33. Box.test(resid(modelauto), type = c("Ljung-Box"))
  34. shapiro.test(resid(modelauto))
  35. jarque.bera.test(resid(model))
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