Evaluation of Indonesian Language Stemmer Algorithms: A Comparative Analysis

Indonesian is a language with a large number of speakers and diverse vocabulary. One of the main challenges of Indonesian language processing is the presence of agglutinative morphology. This complexity makes it challenging for traditional stemming algorithms developed for European languages to accurately handle Indonesian words. This review focuses on several prominent Indonesian text processing algorithms that have been developed specifically for Indonesian, highlighting the contributions made by Nazief and Adriani, Asian, Arifin and Setiono, and the Enhanced Confix Stripping (ECS) stemmer. By examining these algorithms, we can better understand their methodologies, efficacy, and applications. The results of the study revealed that the ECS stemmer outperformed the other algorithms in terms of accuracy and efficiency. The ECS algorithm was able to strip affixes more effectively and accurately identify the root form of words, leading to improved text analysis and information retrieval. As linguistic technology continues to evolve, ongoing research into these methods will be crucial for advancing our ability to process Indonesian texts accurately and effectively.