Enhancing Alumni relations through database: The time-series model for graduates in Kazakhstani university

Abstract

The study examines the potential for growth in the alumni association membership through the increasing number of university graduates. This study focuses on utilizing time series analysis and ARIMA modeling to forecast the number of alumni members in a university association. The growth of student enrollment presents significant potential for the expansion of the alumni association. However, the research reveals that the ratio of alumni association members to the total number of alumni is relatively small for the university under investigation. A literature review corroborates that the comprehensiveness of the university's graduates' database directly influences the willingness of alumni to participate in events and subsequently join the association. The results highlight the paramount importance of improving the database to enhance the conversion rate of alumni into association members. The forecast from two models demonstrates that an enhanced database would lead to an approximately twofold increase in the number of association members. However, a limitation of this study is that the quantitative analysis based on forecast models does not provide specific guidance on how to improve the database or predict the positive or negative effects of potential changes Further research is required to identify specific strategies for improving the database, such as updating contact information and updating employment records, to foster greater alumni participation and increase the number of active association members.