Utilization of Big Data Technology in the Analysis of Academic Data for Students of the Faculty of Computer Science IBI Kosgoro 1957 for Decision Making

Abstract

This research discusses the use of Big Data technology in analyzing student academic data at the Ibi Kosgoro 1957 Faculty of Computer Science with the main aim of optimizing the decision-making process. The main focus of the article is to create a predictive model that can predict student academic success based on extensive data analysis. The research steps involve collecting and processing academic data, including grades, number of courses taken, and other variables that may influence student performance. The collected data is then used to train predictive models using machine learning techniques. The predictive model that is built aims to provide decision-making recommendations to academics. By utilizing Big Data, this article explores deep insights into academic patterns that may be difficult to detect with conventional methods. It is hoped that the research results can make a positive contribution in increasing the efficiency of academic management and help related parties in designing more targeted intervention strategies. In addition, it is hoped that the implementation of this predictive model can support efforts to increase student academic success at the Ibi Kosgoro 1957 Faculty of Computer Science