The development of technology in education is increasing. One technology that is often used in education is big data. This research aims to analyze the factors that influence student performance in test scores. Big Data is a collection of very large and complex data that can be analyzed to reveal useful patterns. In this research, qualitative analysis methods are used to collect and analyze data from various sources, including national and international journals, academic publications, reports, and books. Data processing was conducted using the Kaggle Dataset with a data sample of 1000 students who have taken various exams. This research utilizes Big Data in predicting student performance based on parents' educational background, exam preparation courses, and students' lunch portion. The results show that the factor that affects student performance in exam scores is the student's lunch portion. The number of scores of female students with the appropriate meal portion on the Math, Reading, and Writing exams reached 22.413, 24.875, 24.890. The scores of male students with appropriate lunch portions on the Math, Reading, and Writing exams were 22.759, 21.342, and 20.701. Therefore, the conclusion of this research is that appropriate lunch portions play a crucial role in enhancing students' performance in exam results.