ARIMA, Simple Moving Average, and Exponential Smoothing [closed]

I have time series data about a museum visitors in each month since 2011 to 2019. This data has seasonality. If I want to forecast the visitors in 2020, what forecasting method I should use? ARIMA, Simple Moving Average, or Exponential Smoothing? and why? Thank you :)

The Simple Moving Average and a non-seasonal ARIMA model will not capture seasonality, so if the seasonal signal is strong enough, try Exponential Smoothing with a seasonal component or seasonal ARIMA. (If the seasonal signal is weak, modeling it may make matters worse.) Take a look at the ets() and the auto.arima() functions in the forecast package for R. I strongly recommend Forecasting: Principles and Practice (2nd ed.) by Athanasopoulos & Hyndman.