cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Adam Mudinillah
Contact Email
adammudinillah@staialhikmahpariangan.ac.id
Phone
+6285379388533
Journal Mail Official
adammudinillah@staialhikmahpariangan.ac.id
Editorial Address
Jl. Kampung Koto Dalam, No. 43 RT. 001 RW. 001, Kelurahan Gurun Laweh Kec. Nanggalo Kota Padang, Prov. Sumatera Barat
Location
Kota padang,
Sumatera barat
INDONESIA
International Journal of Research in Counseling
Published by Yayasan Minang Darussalam
ISSN : 29645743     EISSN : 29645735     DOI : https://doi.org/10.55849/ijrc
Core Subject : Education, Social,
Education Social Sciences Other
International Journal of Research in Counseling is an open-access and peer-reviewed journal dedicated to publishing novel research in the field of Counseling. Details on our focus and scope can be viewed here. International Journal of Research in Counseling is published 2 issues per year (June-December) and accepts current research articles that have the potential to make a significant contribution to the exploration and development of counseling and and behavioral sciences. Articles submitted to this journal must display a well-thought-out study design, appropriate data analysis, and interpretation.
Arjuna Subject : Umum - Umum
Articles 44 Documents
 1   2   3   4   5 
Culturally Responsive AI: Designing Emotion Recognition Systems that Account for Diverse Non-Verbal Communication Styles. fuadi, Anwar; Nuwairah, Nahed; Rani , Samsul; Ilham, Ilham; Herlita, Jumi
International Journal of Research in Counseling Vol. 4 No. 1 (2025)
Publisher : Yayasan Minang Darussalam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70363/ijrc.v4i1.274

Abstract

Emotion recognition systems powered by artificial intelligence (AI) have rapidly gained prominence in mental health, education, and human-computer interaction. However, many existing models are built on limited, often Western-centric datasets, which overlook the rich diversity of non-verbal communication across cultures. This paper proposes a culturally responsive AI framework for designing emotion recognition systems that are inclusive of varied facial expressions, gestures, gaze behaviors, and prosodic cues observed in different cultural contexts. Using an interdisciplinary methodology that combines affective computing, cross-cultural psychology, and sociolinguistics, this study analyzes discrepancies in emotional signaling and examines how AI systems can be trained to interpret emotional data in a contextually appropriate way. Findings reveal that culturally insensitive models risk misinterpretation, leading to ethical and practical challenges in real-world applications. The paper offers design principles, ethical considerations, and implementation strategies for developing AI systems that are not only accurate but also equitable and socially aware. This work contributes to ongoing efforts in human-centered AI and highlights the importance of cultural sensitivity in next-generation affective technologies.
The Virtual Supervision Revolution: Enhancing Counselor Competency in Tele-Mental Health Through AI-Enhanced Feedback Systems Ranihusna, Desti
International Journal of Research in Counseling Vol. 4 No. 1 (2025)
Publisher : Yayasan Minang Darussalam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70363/ijrc.v4i1.277

Abstract

The virtual supervision revolution has significantly transformed the way counselor competencies are developed, particularly in the context of tele-mental health services. This study explores the effectiveness of AI-enhanced feedback systems in improving professional skills during online supervision sessions. Using a qualitative research approach involving in-depth interviews and analysis of virtual supervision documentation, the findings reveal that AI integration enables faster, more objective, and structured feedback compared to traditional supervision methods. The system also facilitates enhanced self-reflection, ethical sensitivity, and data-driven decision-making among counselors. These outcomes suggest that AI technology holds great promise in fostering an adaptive, personalized, and sustainable training and supervision ecosystem in the digital era. Nonetheless, concerns related to data privacy, algorithmic accuracy, and technological infrastructure readiness remain critical issues that warrant further investigation.
Early Intervention Strategies for Self-Harm Prevention Using AI-Driven Behavior Tracking in Teenagers Samsinas, Samsinas; Sapirudin, Sapirudin; Widoyo, Heru; Marzuki , Marzuki
International Journal of Research in Counseling Vol. 4 No. 1 (2025)
Publisher : Yayasan Minang Darussalam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70363/ijrc.v4i1.306

Abstract

Self-harm among teenagers has become a critical public health concern, often associated with underlying psychological distress and undetected behavioral patterns. This study explores the development and effectiveness of early intervention strategies for self-harm prevention by utilizing artificial intelligence (AI)-driven behavior tracking systems. By leveraging machine learning algorithms and real-time monitoring tools, the system identifies high-risk behaviors and emotional cues from digital footprints, such as social media activity, messaging patterns, and wearable data. The research adopts a mixed-methods approach, combining behavioral data analysis with expert validation from mental health professionals to enhance predictive accuracy and ethical compliance. Results indicate that AI-based tracking significantly improves the ability to flag early warning signs, enabling timely counseling and intervention. The study contributes to the emerging field of digital mental health by proposing a scalable, proactive solution for youth well-being, while emphasizing the importance of privacy, consent, and multidisciplinary collaboration in its implementation.
Designing AI-Driven Chatbots for Adolescent Mental Health Support in Rural Schools Kasse, Yubina; Riantofani, Riantofani; Rahmi, Siti; Kiftiyah , Kiftiyah
International Journal of Research in Counseling Vol. 4 No. 1 (2025)
Publisher : Yayasan Minang Darussalam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70363/ijrc.v4i1.307

Abstract

Mental health among adolescents in rural schools is increasingly recognized as a critical public health issue, yet these areas often lack access to professional psychological support. This study aims to explore the design considerations and implementation strategies of AI-driven chatbots as accessible and scalable tools for supporting adolescent mental health in rural educational settings. Using a qualitative research design, the study reviews existing literature and analyzes user-centered design principles, AI natural language processing capabilities, and ethical constraints in deploying mental health chatbots. Findings suggest that culturally-sensitive content, confidentiality safeguards, and integration with school counseling protocols are crucial to the effectiveness of such tools. The study proposes a conceptual design framework for future development and implementation. This research contributes to the development of inclusive and adaptive digital interventions in underserved communities.

Page 5 of 5 | Total Record : 44

 1   2   3   4   5 

Filter by Year

2022 2025


Reset
Filter By Issues
All Issue Vol. 4 No. 1 (2025) Vol. 3 No. 2 (2024) Vol. 3 No. 1 (2024) Vol. 2 No. 2 (2023) Vol. 2 No. 1 (2023) Vol. 1 No. 2 (2022) Vol. 1 No. 1 (2022)