Efficiency Analysis of Brute Force and Knuth Morris Pratt Algorithms for Indonesian Keyword Search on KBBI

Keyword search in Indonesian in the Big Indonesian Dictionary (KBBI) is an important problem in the field of information technology, because KBBI is the main reference source in determining the meaning and significance of words in Indonesian. In the keyword search process, there are several algorithms that can be used, one of which is the Brute Force and Knuth Morris Pratt (KMP) algorithms. In this research, we will analyze the efficiency of both algorithms in searching keywords in KBBI. The Brute Force algorithm will compare each character of the keyword with each character in each word in the KBBI. While the KMP algorithm will use a table to match each character in the keyword with each character in each word in the KBBI. The method used for testing the algorithm is to use the KBBI word data set. This test will analyze the running time, memory usage, precision, accuracy, and keyword related of the two algorithms in completing the keyword search in KBBI. The result of this research is a comparison of the complexity and speed of the Knuth Morris Pratt and Brute Force algorithms. The outcomes demonstrate that while searching for keywords in the KBBI, the Brute Force approach is more effective than the KMP algorithm. The Brute Force algorithm has faster execution time, accuracy, and precision compared to the KMP algorithm, the KMP algorithm can be seeded by using less memory than the Brute Force algorithm. So it can be concluded that the Brute Force algorithm is more efficient in searching keywords in the KBBI compared to the KMP algorithm. As a result, the Brute Force algorithm can be utilized as a substitute to quicken the KBBI's keyword search process.