Word Sense Disambiguation (WSD) in Indonesian Sentences Using Simplified Lesk Algorithm

The Indonesian language contains several words with inherent ambiguity, meaning they possess more than one possible interpretation. Word Sense Disambiguation (WSD), a branch of Natural Language Processing (NLP), deals with the challenge of resolving this ambiguity and identifying the precise meaning of a word based on its context. Among the algorithms used for WSD, the Simplified Lesk algorithm stands out as particularly popular. To assess its effectiveness, tests were conducted using the Kamus Besar Bahasa Indonesia (KBBI) as a reference for word definitions, and a dataset of 300 Indonesian sentences containing ambiguous words and their respective meanings as determined by human perception. The research reveals that the configuration of the preprocessing phase plays a crucial role in accurately identifying the intended meaning. After evaluation, the overall accuracy achieved was 58% for the dataset, incorporating preprocessing techniques such as stemming and stopword.