Unlocking Insights: A Literature Review on Enhanced Confix Stripping and Nazief & Adriani Algorithm Modifications for Makassar Language Text Stemming

Abstract

This study investigates the Nazief and Adriani Algorithm and the Enhanced Confix Stripping Stemmer (ECS) in the context of Makassar language. Following a comprehensive investigation, the Nazief & Adriani Algorithm demonstrates proficiency in capturing the complexities of Makassar language by applying numerous morphological criteria. Meanwhile, the Enhanced Confix Stripping Stemmer (ECS) exhibits versatility in dealing with language obstacles, identifying opportunities for further improvement. Using Sastrawi, Confix Stripping, Enhanced Confix Stripping, and Nazief-Adriani, the study emphasizes the need of using linguistically suitable techniques for exact analysis. This work sheds light on improving text processing technology in Makassar language, opening the path for algorithms customized to the language's unique qualities.