Multi Rule-based and Corpus-based for Sundanese Stemmer

Abstract

The purpose of this study is to develop a stemming method by involved several methods including morphological (with affix and pro-lexeme removal), syllable (canonical) pattern, and corpus data as a comparison of the final results of stemming. The algorithm checks a number of the string first and removes affixes, then check the syllable pattern according to the stripping result, then compares to the corpus data which determines the final stemming process. In this study, the corpus data was taken from Sundanese dictionary consists of a single word used for the root word and the extracted dataset from the online Sundanese magazine. The results showed that the stripping of affix and pro-lexeme can remove the corresponding affixes and pro-lexeme then compares words that have a syllable pattern then executes the basic words quickly and the use of corpus can improve accuracy and reduce the over-stemming problems that occur in the stemming process.