Research Arima Model Forecasts Student’s Graduation Rate

Time series data is one of the two main models in data analysis. Time series forecasting is an important class of models in statistics, econometrics, and machine learning. This model is called a time series because the model is applied on particular series with a time element. A time series model usually makes predictions based on the assumption that patterns in the past will repeat in the future. Therefore, building a time series model is that we are modeling the past relationship between the independent variable (the input variable) and the dependent variable (the target variable), based on this relationship to predict the future value of the dependent variable. In this paper, we study the time series model by autoregressive integrated moving average method to predict the graduation rate for the following years to facilitate stakeholders, and management is easy to control and make appropriate strategies.