Comparison of the Efficiency of Bubble Sort and Insertion Sort Algorithms in Sorting Sales Data in Digital Printing

Abstract

The efficacy of the Bubble Sort and Insertion Sort algorithms is analyzed and compared in this study. arrange sorting algorithms in order of how well they perform at analyzing data from digital printing sales. The rate at which data is processed is crucial for information systems in the age of digital revolution, particularly in sectors where transactions must be completed quickly. The selection of the sorting algorithm has been demonstrated by prior research to significantly affect system performance. According to research by Mifortekh (2023), when it comes to arranging sales data for MSMEs, Insertion Sort outperforms Bubble Sort. Furthermore, research by Iskandar (2020) and Vierdansyah et al. (2023) shows that Insertion Sort uses less memory and doesn't need as much data exchange as Bubble Sort. Global Scientific Journal (2022) and Sabah et al. (2023) both acknowledge the steady performance of Insertion Sort in random data sorting, noting that it continues to perform consistently even with increasing dataset size. Using a quantitative approach with secondary data and Python-based simulations, this study examines execution time in an effort to reinforce empirical evidence supporting the supremacy of Insertion Sort over Bubble Sort and help information system developers choose the best sorting algorithm.