Minangkabau Language Stemming: A New Approach with Modified Enhanced Confix Stripping

Minangkabau Language Stemming: A New Approach with Modified Enhanced Confix Stripping

enhanced confix stripping; minangkabau language; morphological; natural language processing; stemming

Stemming is an essential procedure in natural language processing (NLP), which involves reducing words to their root forms by eliminating affixes, including prefixes, infixes, and suffixes. The employed method assesses the efficacy of stemming, which differs according to language. Complex affixation patterns in Indonesian and regional languages such as Minangkabau pose considerable difficulties for traditional algorithms. This research adopts the enhanced fixed-stripping method to tackle these issues by integrating linguistic characteristics unique to Minangkabau. This study has three phases: data acquisition, pseudocode development, and algorithm execution. Testing revealed an average accuracy of 77.8%, indicating the algorithm's proficiency in managing Minangkabau’s intricate morphology. Nevertheless, constraints persist, particularly with irregular affixationpatterns. Possible improvements could include adding more datasets, improving the rules for handling affixes, and using machine learning to make the system more flexible and accurate. This study emphasizes the significance of customized solutions for regional languages and provides insights into the advancement of NLP in various linguistic environments. The findings underscore the progress made in processing Minangkabau text while also emphasizing the need for further research to address current issues

Fadhli Almu’iini Ahda1, Aji Prasetya Wibawa2*, Didik Dwi Prasetya3,Danang Arbian Sulistyo4, Andrew Nafalski

https://jurnal.iaii.or.id/index.php/RESTI/article/view/6511/1092

Elecrtrical Engineering and Informatics, Universitas Negeri Malang, Malang, Indonesia

June 23, 2025

FAJAR BAGUS W

PDF

ENGLISH

TEXT