Comparative Analysis of Searching and Sorting Algorithms in Student Data Processing

Abstract

Efficient data processing is crucial, especially in searching and sorting large volumes of student data. This study aims to analyze and compare the performance of four algorithms: Linear Search, Binary Search, Bubble Sort, and Quick Sort, in student data processing. The experiments were conducted using datasets of 1,000, 5,000, and 10,000 student records. The results show that Quick Sort delivers the best performance in sorting tasks with the fastest execution time, while Binary Search demonstrates high efficiency in searching within sorted datasets. In contrast, Bubble Sort and Linear Search exhibit poor performance as the dataset size increases. This study recommends the use of Quick Sort for sorting and Binary Search for searching in large-scale data processing.