Separation of Basic Words in Angkola Batak Text Documents using Enhanced Confix Stripping Stemmer Case: Mandailing Ethnic

Abstract

Abstract Stemming is the process of separating essential words from an affixed word. Stemming works by eliminating morphological variations which attached to a word by removing affixes in a word with a dictionary as a reference to the stemming process. One effective algorithm for resolving stemming in Indonesian is an Enhanced Confix Stripping Stemmer algorithm. In this case, the improved Confix stripping stemmer algorithm is implemented for the separation of essential words in the Angola-Mandailing Batak language document that has different phonologies and morphologies with Indonesian. The documents used are Latin character documents in the Angkola-Mandailing language that goes through the stages of filtering, folding cases, and tokenization before stemming. The stemming process is done by removing particles, ownership, suffixes, and prefixes. After testing this research, it was concluded that this algorithm was able to separate essential words in the Angkola-Mandailing Batak language with accuracy 87,05%.