Student Employment Algorithm of Private Universities Based on Artificial Intelligence and Time Series Decomposition

Employment rate is one of the key indicators of private colleges and universities. With the employment difficulties of college graduates becoming more and more prominent, how to effectively predict the employment situation of graduates has been paid more and more attention by college students and employment guidance departments. This paper uses an artificial intelligence module and STL time series model to analyze employment. Good results were achieved, and the data prediction was accurate, reaching 95.72%. This study identified H County of Shandong Province as a case, analyzed the implementation status of university employment supervision and explored its improvement strategies, which can provide inspiration and reference for national university employment.