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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)
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')
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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