Implementation of Dictionary Lookup and Damerau-Levenshtein Distance for Correcting Non-Standard Indonesian and English Terms

Abstract

Indonesian, as the official language, follows the standards set by the Kamus Besar Bahasa Indonesia. Despite this, academic writing often contains errors such as non?standard word usage, typographical mistakes, and contextually inappropriate foreign terms. This study presents a web?based application for detecting and correcting non?standard words in scholarly documents, employing a Dictionary Lookup approach (referencing both the KBBI and English IT terminology) alongside the Damerau?Levenshtein Distance algorithm. Evaluation on 100 test entries yielded 100% detection accuracy, 98% precision, and 100% recall. Processing times averaged 0.03 seconds for 50 standard words and 57.13 seconds for 50 non?standard words. Incorporating frequency?based ranking improved the relevance of suggestions, with correct corrections most often appearing first. A maximum edit distance of two was identified as optimal, balancing accuracy and efficiency in User Acceptance Testing.