The Accuracy of Artificial Intelligence in Processing Formal Javanese within Essay Texts: Strengths, Limitations, and Implications for Language Preservation
Keywords:
Artificial Intelligence, Natural Language Processing, Javanese language, Formal communication, Low-resource languagesAbstract
This research explores the capacity of Artificial Intelligence (AI), particularly Natural Language Processing (NLP) models, in handling formal Javanese within essay text. As one of Indonesia’s largest regional languages, Javanese holds complex grammatical structures and politeness registers (ngoko, madya, krama), which pose challenges for computational processing. While AI systems show promising strengths in general syntax comprehension and vocabulary recognition, their accuracy significantly decreases when dealing with formal Javanese, especially in contexts requiring cultural sensitivity and hierarchical politeness. The methodology employed combines corpus-based analysis with AI evaluation, measuring the ability of models to generate, interpret, and classify formal Javanese expressions in essay texts. The results indicate that AI performs adequately in structural tasks but struggles with nuanced elements such as social deixis, politeness strategies, and context-driven interpretation. These weaknesses primarily reflect data scarcity, training bias, and the underrepresentation of Javanese in large-scale multilingual datasets. The findings suggest that AI can play a vital role in education, government, and business communication, as well as in the preservation and revitalization of the Javanese language, provided that richer and culturally embedded datasets are developed. This research concludes that interdisciplinary collaboration between technologists, linguists, and cultural experts is essential to maximize the potential of AI for low-resource languages such as Javanese.
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