<![CDATA[This study aims to analyze the performance of three fundamental sorting algorithms—Bubble Sort, Selection Sort, and Insertion Sort—implemented using the Python 3.12.10 programming language. The experiment was conducted using five dataset sizes consisting of student data with 50, 100, 150, 200, and 250 records. Each algorithm was tested under three data order conditions: random, nearly sorted, and reversed. The experimental results indicate that Insertion Sort achieved the most efficient execution time for nearly sorted data, averaging below one millisecond, while Bubble Sort exhibited the slowest performance, particularly on reversed data, with execution times exceeding 30 milliseconds. Selection Sort maintained consistent performance across conditions but remained slower than Insertion Sort in most cases. Overall, the empirical findings support the theoretical O(n²) time complexity and reinforce the learning of algorithm efficiency concepts in the Algorithm and Data Structure course of the Information Technology Study Program.]]>
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