IMPLEMENTATION OF REGIONAL LANGUAGE AI CHATBOTS FOR LOCAL CROSS-CULTURAL COMMUNICATION

Abstract

This research is important to determine the extent to which regional language AI chatbots can support local cross-cultural communication effectively. In addition, this research can also identify obstacles and challenges faced in the implementation of regional language chatbots. The purpose of this research is to implement AI chatbots that use regional languages in the context of local cross-cultural communication and to determine the ability of regional language AI chatbots to convey messages effectively and in accordance with local cultural values. This research uses a qualitative approach with a qualitative descriptive method. This research was conducted in a local community or community environment that uses regional languages. The informant determination technique in this study uses purposive sampling. Data collection techniques use in-depth interviews and observations. Data analysis techniques are carried out interactively and continuously, following the qualitative data analysis model proposed by Miles, Huberman. Data wetness techniques use source triangulation, techniques and member checks. The main findings focus on the implementation of Artificial Intelligence (AI)-based chatbots that use regional languages as a medium of communication with local communities. This chatbot is used as a means of conveying information and interaction with users from diverse local cultural backgrounds. The conclusion of this study is that implementing regional language AI chatbots involves not only the technical aspects of system development but also an understanding of the local social and cultural context. The use of Artificial Intelligence technology, particularly Natural Language Processing, enables chatbots to understand and respond to regional languages more naturally and contextually.