Knuth Morris Pratt Algorithm in Enrekang-Indonesian Language Translator

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Desi Anggreani, Desy Pratiwi Ika Putri, Anik Nur Handayani, Huzain Azis

2020 4th International Conference on Vocational Education and Training, ICOVET 2020 Conference paper Cited by 5 Quartile

Abstract

String match search as in the case of making a translator matching accuracy is essential. Therefore, there needs to be an implementation of a string matching algorithm that will help get accurate and optimal results. Knuth Morris Pratt is one algorithm to solve problems in the case of string matching. The workings of the KMP algorithm match character by character between pattern and text in the repository. The results of this study indicate that the accuracy of string matching with input in the form of letters and characters by mixing punctuation is 100%. By using 1063 vocabularies, the implementation of the Knuth Morris Pratt algorithm in the Indonesian enrekang language translator has an average processing time of 0.01901 milliseconds and average memory usage of 15,768 MB so that the KMP algorithm can be implemented optimally in the enrekang-Indonesian language translator. © 2020 IEEE.

Affiliations

State University of Malang, Department of Electrical Engineering, Malang, Indonesia; Universitas Muslim Indonesia, Faculty of Computer Science, Makassar, Indonesia