Systematic literature review demonstrates varied stemming algorithm adoption across Ambon Malay texts, highlighting Nazief Adriani as the predominant method for base word recovery.
Key Points
Stemming algorithms show distinct adoption frequencies across Ambonese text analyses, with specific affix removal techniques guiding morphological parsing.
Nazief Adriani emerged as the most frequent method with 17 recorded cases, whereas Enhanced Confix Stripping appeared in 12 identified applications.
Systematic literature review of 127,000 dictionary base words highlights algorithm selection trade-offs, supporting improved text processing frameworks.