Stemming in Ambonese posed a significant challenge due to its extensive lexicon, encompassing approximately 127,000 base words as recorded in the Kamus Besar Bahasa Indonesia (Indonesian Dictionary). This complexity arises from the task of extracting base words from those with affixes, necessitating the removal of various affixes such as prefixes, infixes, suffixes, and their combinations. This process greatly influences analytical outcomes. To address this linguistic complexity, several stemming algorithms were developed. These include Nazief Adriani, Enhanced Confix Stripping, Sastrawi, and Tala, each offering unique techniques to handle stemming complexities in Indonesian. The selection of the appropriate algorithm is crucial for ensuring the accuracy and reliability of the stemming process within the analytical framework. In conducted stemming research, there were variations in methods used. The most frequently used algorithm was Nazief Adriani, with 17 recorded cases, followed by Enhanced Confix Stripping with 12 cases. Sastrawi, although less frequent, was used in 4 cases, while Tala appeared in 1 case. This diversity reflects the available choices in selecting a fitting stemming method. However, this may relate to factors such as ongoing research projects, funding availability, or other external conditions affecting research production during that period. Consequently, stemming research remains an interesting and relevant topic, with the potential for continued growth and significant contributions to text processing and linguistic research in the future.