Club recruitment activities are an important way for universities to carry out campus cultural construction and student organizations,and are an important component of campus culture.However, due to the randomness of club members, there are problems with the accuracy of predicting the number of applicants and the effectiveness of resource allocation in predicting the number of university club members during the recruitment process. This article conducts a questionnaire survey analysis on students' acceptance of club activities and their participation in club activities at different time points.It utilized the Autoregressive Integrated Moving Average Model (ARIMA) in time series analysis algorithms to design a data prediction model for club recruitment, and analyzed the university club recruitment model. Research has shown that the club recruitment prediction model designed based on ARIMA in this article can achieve a maximum accuracy of 96.7% and optimize resource allocation.

Club recruitment;Autoregressive moving average model;Residual analysis;Resource allocation optimization

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DOI： https://doi.org/10.62639/sspjinss03.20240104

Published： 2024