<![CDATA[Data sorting is a fundamental process in managing sales information within micro, small, and medium enterprises (MSMEs). The choice of an appropriate sorting algorithm significantly impacts the efficiency of information systems, particularly in terms of execution time and the number of comparisons. This study aims to compare the performance of two classic sorting algorithms—Bubble Sort and Insertion Sort—in sorting MSME sales data. A quantitative experimental method was employed, with testing conducted on datasets ranging from 100 to 10,000 transactions under three initial data conditions: random, ascending, and descending. The results indicate that Insertion Sort consistently outperforms Bubble Sort in both execution time and the number of comparisons, especially for small to medium-sized data. Insertion Sort also demonstrates better adaptability to partially sorted data. Based on these findings, Insertion Sort is recommended for use in MSME sales information systems where data volumes are relatively small to moderate. This study also opens opportunities for further research on more advanced algorithms for large-scale data processing in the future.]]>
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