Data-Based Islamic Education Management Utilizes Big Data to Improve the Quality of Education

Abstract

Islamic education played a crucial role in shaping students' character and intellectual development. However, challenges in data management and improving learning quality remained significant obstacles. The implementation of big data offered an innovative solution to optimize Islamic education management through more accurate and efficient data-driven analysis. This study aimed to explore how the utilization of big data improved the quality of Islamic education by analyzing its impact on students' academic performance, administrative efficiency, and user satisfaction. This study employed a mixed-methods approach, combining qualitative methods through case studies and in-depth interviews with quantitative methods through surveys and statistical analysis using SPSS. Data were collected from several Islamic educational institutions that had implemented big data in their management systems. The findings indicated that the implementation of big data increased students' academic performance by 15%, enhanced administrative efficiency by 30%, and improved user satisfaction by up to 20%. Regression analysis showed that big data contributed 56% to the improvement of education quality, with correlation test results (r = 0.75, p < 0.05) and t-test results (t = 6.21, p < 0.01) indicating a significant difference before and after implementation. This study suggested that the utilization of big data could enhance the effectiveness of Islamic education management and drive digital transformation in the learning system. However, challenges such as inadequate infrastructure and limited human resources needed to be addressed to ensure optimal implementation. Future research should further explore more specific big data management models for Islamic education and develop policy strategies to overcome technological and data security challenges.