Pengembangan Asisten Virtual Berbasis NLP untuk Mendukung Kesejahteraan Psikologis Mahasiswa

Muhammad Tafazzani Addien; Yuyun Umaidah; Apriade Voutama

doi:10.31004/riggs.v5i2.10114

Authors

Muhammad Tafazzani Addien Universitas Singaperbangsa Karawang
Yuyun Umaidah Universitas Singaperbangsa Karawang
Apriade Voutama Universitas Singaperbangsa Karawang

DOI:

https://doi.org/10.31004/riggs.v5i2.10114

Keywords:

Asisten Virtual, Chatbot, Natural Language Processing, Dukungan Emosional, Kesejahteraan Psikologis Mahasiswa

Abstract

Peningkatan tekanan akademik, sosial, dan personal pada mahasiswa menimbulkan kebutuhan terhadap media pendampingan psikologis awal yang mudah diakses, aman, responsif, dan tidak menghakimi. Penelitian ini bertujuan mengembangkan asisten virtual berbasis Natural Language Processing (NLP) untuk mendukung kesejahteraan psikologis mahasiswa melalui interaksi berbasis teks. Metode penelitian menggunakan Research and Development dengan model Prototype yang meliputi analisis kebutuhan, perancangan arsitektur, implementasi modul NLP, pengujian fungsi, dan evaluasi pengguna. Sistem dirancang menggunakan komponen antarmuka chatbot, preprocessing teks, klasifikasi intent, analisis sentimen, basis pengetahuan kesehatan mental, serta manajemen dialog. Hasil pengembangan menunjukkan bahwa sistem mampu menerima pesan pengguna, mengenali keluhan akademik dan emosional, memproses bahasa informal, memberikan respons suportif, serta menampilkan arahan menuju konselor atau layanan profesional ketika diperlukan. Pengujian black box memperlihatkan bahwa fungsi pengiriman pesan, klasifikasi intent, analisis sentimen, pemilihan respons, penanganan pesan di luar konteks, dan penyajian informasi konseling berjalan sesuai rancangan. Evaluasi pengguna menunjukkan bahwa asisten virtual dinilai bermanfaat sebagai media pendampingan awal karena fleksibel, cepat, dan membantu proses refleksi emosional. Meskipun demikian, sistem masih memerlukan perluasan dataset percakapan, peningkatan pemahaman bahasa slang dan konteks panjang, perlindungan privasi, serta mekanisme deteksi risiko. Asisten virtual tidak menggantikan psikolog atau konselor, tetapi dapat menjadi pintu awal menuju dukungan profesional yang lebih aman dan berkelanjutan.

Downloads

Download data is not yet available.

References

1. Hianto, S., & Shanti, I. (2018). Dinamika Stres , Strategi Coping , dan Dukungan Sosial yang Diharapkan Mahasiswa Skripsi di Universitas XYZ. Provite: Jurnal Psikologi Pendidikan, 11(2), 41–60.

2. Marhamah, Zahara, Fhadhillah, P., Aura, R., & Salat, D. S. J. (2023). PENGARUH DESAIN GRAFIS TERHADAP HUMAN DAN COMPUTER INTERACTION DALAM APLIKASI WEBSITE. TECHSI, 14(2), 136–143.

3. Yuniarni, Pratama, Y. B., & Pramudyantoro, A. (2025). Pengembangan Virtual Assistant menggunakan Teknologi NLP dengan Metode Algoritma Machine Learning untuk Layanan Informasi Akademik di SMA Negeri 1 Parittiga Berbasis Web Yuniarni1*,. Mars: Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer, 3(September). https://doi.org/Mars: Jurnal Teknik Mesin, Industri, Elektro dan Ilmu Komputer Volume 3, Nomor 5, Oktober 2025 e-ISSN : 3031-8742, p-ISSN : 3031-8750, Hal. 205-219 DOI:

4. https://doi.org/10.61132/mars.v3i5.1152

5. Boucher, E. M., Harake, N. R., Ward, H. E., Stoeckl, S. E., Vargas, J., Minkel, J., Parks, A. C., & Zilca, R. (2021). Artificially intelligent chatbots in digital mental health interventions: A review. Expert Review of Medical Devices, 18(sup1), 37–49. https://doi.org/10.1080/17434440.2021.2013200

6. Broadbent, M., Medina Grespan, M., Axford, K., Zhang, X., Srikumar, V., Kious, B., & Imel, Z. (2023). A machine learning approach to identifying suicide risk among text-based crisis counseling encounters. Frontiers in Psychiatry, 14, 1110527. https://doi.org/10.3389/fpsyt.2023.1110527

7. Deshpande, S., & Warren, J. (2021). Self-harm detection for mental health chatbots. Studies in Health Technology and Informatics, 281, 48–52. https://doi.org/10.3233/SHTI210118

8. He, Y., Yang, L., Zhu, X., Wu, B., Zhang, S., Qian, C., & Tian, T. (2023). Conversational agent interventions for mental health problems: Systematic review and meta-analysis of randomized controlled trials. Journal of Medical Internet Research, 25, e43862. https://doi.org/10.2196/43862

9. Klos, M. C., Escoredo, M., Joerin, A., Lemos, V. N., Rauws, M., & Bunge, E. L. (2021). Artificial intelligence-based chatbot for anxiety and depression in university students: Pilot randomized controlled trial. JMIR Formative Research, 5(8), e20678. https://doi.org/10.2196/20678

10. Li, H., Zhang, R., Lee, Y.-C., Kraut, R. E., & Mohr, D. C. (2023). Systematic review and meta-analysis of AI-based conversational agents for promoting mental health and well-being. npj Digital Medicine, 6, 236. https://doi.org/10.1038/s41746-023-00979-5

11. Lim, S. M., Shiau, C. W. C., Cheng, L. J., & Lau, Y. (2022). Chatbot-delivered psychotherapy for adults with depressive and anxiety symptoms: A systematic review and meta-regression. Behavior Therapy, 53(2), 334–347. https://doi.org/10.1016/j.beth.2021.09.007

12. Liu, H., Peng, H., Song, X., Xu, C., & Zhang, M. (2022). Using AI chatbots to provide self-help depression interventions for university students: A randomized trial of effectiveness. Internet Interventions, 27, 100495. https://doi.org/10.1016/j.invent.2022.100495

13. Maples, B., Cerit, M., Vishwanath, A., & Pea, R. (2024). Loneliness and suicide mitigation for students using GPT3-enabled chatbots. npj Mental Health Research, 3, 4. https://doi.org/10.1038/s44184-023-00047-6

14. Shah, J., DePietro, B., D’Adamo, L., Firebaugh, M.-L., Laing, O., Fowler, L. A., Smolar, L., Sadeh-Sharvit, S., Taylor, C. B., Wilfley, D. E., & Fitzsimmons-Craft, E. E. (2022). Development and usability testing of a chatbot to promote mental health services use among individuals with eating disorders following screening. International Journal of Eating Disorders, 55(9), 1229–1244. https://doi.org/10.1002/eat.23798

15. Taylor, M. E., Liu, M., Abelson, S., Eisenberg, D., Lipson, S. K., & Schueller, S. M. (2024). The reach, effectiveness, adoption, implementation, and maintenance of digital mental health interventions for college students: A systematic review. Current Psychiatry Reports, 26(12), 683–693. https://doi.org/10.1007/s11920-024-01545-w

16. Ulrich, S., Lienhard, N., Künzli, H., & Kowatsch, T. (2024). A chatbot-delivered stress management coaching for students (MISHA app): Pilot randomized controlled trial. JMIR mHealth and uHealth, 12, e54945. https://doi.org/10.2196/54945

17. Vereschagin, M., Wang, A. Y., Richardson, C. G., Xie, H., Munthali, R. J., Hudec, K. L., Leung, C., Wojcik, K. D., Munro, L., Halli, P., Kessler, R. C., & Vigo, D. V. (2024). Effectiveness of the Minder mobile mental health and substance use intervention for university students: Randomized controlled trial. Journal of Medical Internet Research, 26, e54287. https://doi.org/10.2196/54287

18. World Health Organization. (2021). Ethics and governance of artificial intelligence for health: WHO guidance. World Health Organization. https://www.who.int/publications/i/item/9789240029200

19. Xu, Z., Xu, Y., Cheung, F., Cheng, M., Lung, D., Law, Y.-W., Wong, P. W. C., & Yip, P. S. F. (2021). Detecting suicide risk using knowledge-aware natural language processing and counseling service data. Social Science & Medicine, 283, 114176. https://doi.org/10.1016/j.socscimed.2021.114176