Abstract
This research paper predicts the period of mobilization of graduated student during their NYSC by detecting the frequent sub sequences in a sequence database and observing the values that a variable takes at a different time. This paper explores the application of Machine Learning for predicting of NYSC mobilization period. Numerous factors or factors affect the prediction of the time series such as the pre-mobilization period, the year, batch and registration period served as the variable used for predicting. The data for the study was obtained from various website like www.nairaland.com, www.portal.nysc.org.ng, www.nigeriaschool.com.ng, www.myschoolgist.com, www.myschool.ng, www.hotnigerianjobs.com, www.corpr.com.ng, www.myjobmag.com, www.aaua.edu.ng, www.ngcareers.com, Preprocessing steps were adopted to convert the data into a usable form. After this, the Autoregressive Integrated Moving Average (ARIMA) model was built, the data were split into training and testing data and the model was evaluated giving an accuracy of 86.8%. Keywords: NYSC, Posting, Mobilization, Registration, ARIMA Model, Time Series, Batch, Graduating Students.
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