<![CDATA[Fast and accurate information retrieval for thesis titles is crucial within the academic environment of Universitas Bina Darma to prevent research duplication. The massive increase in data volume demands the implementation of mathematically efficient string matching algorithms. This study aims to compare the performance of the Brute Force and Rabin-Karp algorithms in executing exact matching on a dataset of thesis titles. A quantitative experimental approach was utilized by executing and isolating pure logic computation within a Node.js environment. Measurements focused on execution time and the number of character comparison operations across variations in keyword length, data volume, and worst-case scenarios. Experimental results demonstrate that the Brute Force algorithm consistently outperforms Rabin-Karp in terms of execution speed. In the worst-case scenario, Brute Force required only 20.0970 ms to confirm that a pattern was not found, whereas Rabin-Karp required 42.4836 ms. Based on the comprehensive empirical data, Brute Force is concluded to be the most optimal algorithm for the text characteristics of the thesis title dataset at Universitas Bina Darma, while Rabin-Karp remains advantageous in reducing the number of character comparison operations.]]>
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