Development of an Interactive Smart Chatbot Application as a Local Language Based Educational Media for HIV/AIDS Prevention Nabela Putri Yanuari (a*), Muhamad Rosidin (b), Iik Sartika (a), Yuditha Nindya Kartika Rizqi (a), Arih Diyaning Intiasari (a), Eky Susilowati (a), Nasya Adelia Putri (a), Rokhayati (c), Agniya Thahira (b)
a) Faculty of Health Sciences, Jenderal Soedirman University
Jl.. Dr. Soeparno, Karangwangkal, Karang Bawang, Grendeng, Kec. Purwokerto Utara, Purwokerto, Jawa Tengah, Indonesia
b) Faculty of Technology and Health Sciences, Siber Muhammadiyah University
Pakuncen, Wirobrajan, Kota Yogyakarta, Daerah Istimewa Yogyakarta
c) Faculty of Science Technology and Health, Islam Mulia University
Jl. Wates No.Km 9, RW.5, Plawonan, Argomulyo, Kec. Sedayu, Kabupaten Bantul, Daerah Istimewa Yogyakarta, Indonesia
Abstract
Background: HIV/AIDS prevention education is essential to reduce infection rates and stigma, supporting the achievement of the SDGs goal to end the HIV/AIDS epidemic. However, in Indonesia, gaps in access, social stigma, and language barriers still hinder communities from obtaining accurate information about HIV/AIDS. The advancement of digital technology opens new opportunities through the use of chatbots, which can provide personalized, anonymous, and responsive information while overcoming linguistic challenges.
Purpose: This study aims to design and develop an interactive chatbot application based on Telegram that can provide education about HIV/AIDS using local language.
Methods: This research uses a software development approach with a prototyping method. The research stages include system requirements analysis, prototype design, implementation, testing, and evaluation. The smart chatbot application is developed using the Python programming language, integrating two main services: Google Generative AI via API Key from Google AI Studio and the Telegram Bot API with a token obtained from the @BotFather service.
Results: The interactive smart chatbot application was successfully developed and integrated with the Telegram platform. Initial testing revealed high user engagement and accurate information delivery in local languages such as Javanese and Sundanese. The chatbot effectively handled queries by utilizing Google Generative AI, providing personalized and responsive responses to HIV/AIDS prevention education needs.
Conclusion: The research findings indicate that a local language-based interactive smart chatbot can serve as an educational medium for HIV/AIDS prevention, thereby contributing to the achievement of the SDGs target to end the HIV/AIDS epidemic through innovative digital health education.
Keywords: HIV/AIDS Prevention, Interactive Chatbot, Telegram Bot, Local Language, Digital Health Education
