Penggunaan Big Data dalam Pengambilan Keputusan Akademik dan Manajemen Pendidikan

Abstract

This study aims to analyze the use of big data in academic decision-making and educational management, and to identify the benefits and challenges of its implementation. The study employed a literature study method by reviewing scientific articles, books, and proceedings published between 2019 and 2025. Literature was obtained through scientific databases such as Google Scholar, Scopus, and ScienceDirect using keywords such as big data, learning analytics, educational data mining, and educational management. The literature selection process involved identification, screening based on title and abstract relevance, assessing eligibility based on topic suitability, and analyzing sources that met the inclusion criteria. Data were analyzed qualitatively using content analysis techniques to identify key themes. The study results indicate that the use of big data supports data-driven decision-making through learning analytics, predicting academic achievement, early identification of at-risk students, personalized learning, and increasing the efficiency of educational resource management. However, its implementation still faces challenges in the areas of data privacy protection, information security, technological infrastructure readiness, data quality, and human resource competency. These findings indicate that the successful implementation of big data in education requires the support of data governance, clear policies, and strengthening technological and human resource capacity.