Development of natural language processing on morphologybased Minangkabau language stemming algorithm

Minangkabau language (ML) is one of the daily communication tools used by people West Sumatra, Indonesia. ML a challenge in communicating. The translation process necessary to facilitate communication. This study aims build system for into Indonesian developing concept natural processing (NLP). NLP development adopts performance morphology-based stemming algorithm (MLSA) which can separate basic words with affixes and endings. research dataset 600 sourced from big dictionary. results this provide analytic output that translate well. These are presented based on testing word input an accuracy rate 97.16% text documents 91.65%. Thus, MLSA presents process. Based these results, contributes model carrying out removing prefixes, inserts, suffixes language. Overall, be useful as tool translating Indonesian.