  This study provides an overview of the history of the development of Natural
Language Processing (NLP) in the context of the Indonesian language, with a
focus on the basic technologies, methods, and practical applications that have
been developed. This review covers developments in basic NLP technologies such
as stemming, part-of-speech tagging, and related methods; practical
applications in cross-language information retrieval systems, information
extraction, and sentiment analysis; and methods and techniques used in
Indonesian language NLP research, such as machine learning, statistics-based
machine translation, and conflict-based approaches. This study also explores
the application of NLP in Indonesian language industry and research and
identifies challenges and opportunities in Indonesian language NLP research and
development. Recommendations for future Indonesian language NLP research and
development include developing more efficient methods and technologies,
expanding NLP applications, increasing sustainability, further research into
the potential of NLP, and promoting interdisciplinary collaboration. It is
hoped that this review will help researchers, practitioners, and the government
to understand the development of Indonesian language NLP and identify
opportunities for further research and development.
