Implementation of Not So Naive and Burkhard-Keller Tree algorithms in Indonesian-Hokkien dictionary application

Abstract

Abstract In Indonesia, especially in Medan, North Sumatra, Hokkien is used in everyday life within the Chinese community. However, learning the language is still done manually. Therefore, the authors intend to create an Android-based Hokkien dictionary application. The most common typing errors found were deleting and inserting single characters, substituting and reversing adjacent characters. Exact string matching can perform a quick search, but the search will fail when the incorrect input is entered. This study aims to prove the advantages and disadvantages of each algorithm in accessing information in addition to displaying the results of the running time of both algorithms. The results showed that the search time for the Burkhard-Keller Tree algorithm increased by 72% and 96% for the Not So Naive algorithm when searching on a database containing 200 words and 400 words. The Not So Naive algorithm has a mean running time of 26.9 ms and a mean running time of 53.5 ms on the Burkhard-Keller Tree algorithm.