DERET WAKTU

library(tseries)
library(forecast)

Data = DATA_EMONEY
#tsData = ts(as.numeric(Data$Jumlah), start=c(2009, 1), end=c(2019,10), frequency=12)
tsData = ts(as.numeric(Data$Jumlah), start=c(2009, 1), end=c(2019,10), frequency=12)
summary(tsData)
boxplot(tsData)
t.test(tsData, conf.level = 0.95)
sd(tsData)
var(tsData)
ts.plot(tsData, ylab='Jumlah Transaksi (satuan Transaksi)', xlab='Waktu (Bulan)', main='Jumlah Transaksi Uang Elektronik di Indonesia')
#par(new=TRUE)
#ts.plot(tsData)
adf.test(tsData)
tsDatadiff = diff(tsData, difference = 50)
ts.plot(tsDatadiff,ylab='Jumlah Transaksi (satuan Transaksi)', xlab='Waktu (Bulan)',main='Differensiasi 1 Jumlah Transaksi Uang Elektronik di Indonesia')
adf.test(tsDatadiff)
model = arima(tsData, order = c(4,2,3))
model
arima(tsData, order = c(4,2,3))
model = arima(tsData, order = c(6,4,2))
#arima(tsData, order = c(3, 50, 0))

modelauto = auto.arima(tsData)

acf(tsDatadiff, main='Plot ACF Data Differensiasi 2')
pacf(tsDatadiff, main='Plot PACF Data Differensiasi 2')

fcast = forecast(modelauto, h = 14, level = 0.95)
plot(fcast)

Box.test(resid(modelauto), type = c("Ljung-Box"))
shapiro.test(resid(modelauto))
jarque.bera.test(resid(model))