Perancangan Arsitektur Kecerdasan Buatan "Bubu": Agen Pendamping PsikososialMahasiswa Berbasis Multimodal dan Kearifan Lokal
DOI:
https://doi.org/10.22236/teknoka.v10i1.22717Keywords:
Artificial Intelligence, Mental Health, Multimodal, Prompt Engineering, Student ChatbotAbstract
The mental well-being of Indonesian university students is currently facing complex pressures, ranging from heavy academic demands to economic instability and the psychological impacts of social media interactions. Unfortunately, the availability of professional psychologists is not commensurate with the population in need, creating a significant service gap. This study aims to design "BUBU," a web-based artificial intelligence agent positioned as a first-line defense for psychosocial support. The system is developed using a Human-Centered Design approach, integrating multimodal inputs (text, voice, and visuals) to detect user emotions in real-time. BUBU is trained using a Large Language Model (LLM) with prompt engineering techniques that adopt student vernacular (slang/code-mixing) and Active Listening protocols. Test results show that the system is capable of providing contextual emotional validation, adjusting response tones based on facial expressions, and possesses a fail-safe mechanism to detect suicide risks and provide appropriate referrals. This prototype offers potential as an effective mental health triage tool in campus environments.
Downloads
References
A. E. Wahdi, S. A. Wilopo, and H. E. Erskine, "The Prevalence of Adolescent Mental Disorders in Indonesia: An Analysis of Indonesia – National Mental Health Survey (I-NAMHS)," Journal of Adolescent Health, vol. 72, no. 3, p. S1, 2023.
A. A. Rivaldi, "Analisis Faktor Penyebab Stres pada Mahasiswa dan Dampaknya Terhadap Kesehatan Mental," Detector: Jurnal Inovasi Riset Ilmu Kesehatan, vol. 2, no. 4, pp. 11–18, 2024.
A. Khairan, et al., "Chatbot AI dalam Identifikasi Awal Gangguan Kesehatan Mental di Indonesia: Tantangan dan Prospek," Jurnal Empati, vol. 13, no. 6, pp. 1–10, 2024.
H. Chin, et al., "The Potential of Chatbots for Emotional Support and Promoting Mental Well-Being in Different Cultures: Mixed Methods Study," Journal of Medical Internet Research, vol. 25, p. e43632, 2023.
A. I. Wibowo, et al., "Fenomena Bahasa Anak Jakarta Selatan di Twitter," dalam Prosiding Seminar Nasional Linguistik dan Sastra (SEMNALISA), Denpasar, 2021, pp. 60–65.
A. Aggarwal, et al., "Artificial intelligence–based chatbots for promoting health behavioral changes: Systematic review," Journal of Medical Internet Research, vol. 25, p. e40789, 2023.
Gemini Team, Google, "Gemini: A Family of Highly Capable Multimodal Models," arXiv preprint arXiv:2312.11805, 2023.
T. Kulik, et al., "Effectiveness of artificial intelligence chatbots on mental health & well-being in college students: a rapid systematic review," Frontiers in Digital Health, vol. 6, 2024.
I. Y. Suryaputri, R. Mubasyiroh, S. Idaiani, and L. Indrawati, "Determinants of Depression in Indonesian Youth: Findings from a Community-based Survey," Journal of Preventive Medicine and Public Health, vol. 55, no. 1, pp. 88–97, 2022.
S. Onie, et al., "Indonesia’s first suicide statistics profile: an analysis of suicide and attempt rates, underreporting, and methods in five provinces," The Lancet Regional Health - Southeast Asia, vol. 22, p. 100344, 2024.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Prosiding Seminar Nasional Teknoka

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.



Supported by :



