Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Ghita Athalina
Universitas Sriwijaya
Computer Science & IT Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Mapping global ethical AI principles into Indonesian higher education: a framework for responsible institutional implementation Zaqqi Yamani; Sarifah Putri Raflesia; Dinda Lestarini; Ghita Athalina; Purwita Sari
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 3: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i3.pp2053-2061

Abstract

Artificial intelligence (AI) is an essential component of higher education's digital revolution. But its application unlocks a chain of ethics issues that must be resolved in an organized manner. This study uses mapping between United Nations Educational, Scientific, and Cultural Organization (UNESCO) and Organisation for Economic Co-operation and Development (OECD) guidelines and illustrates whether both guidelines can actually be implemented by Indonesian universities. In this study, a literature review and analysis of the content of the AI policy framework at the international level were conducted which were then applied to understand the operating environment in higher education. The findings in this study emphasize eight contextually meaningful ethical norms such as fairness, transparency, accountability, data protection, sustainability, inclusion, AI literacy, and ethical governance. Each of these values is combined with real-world practices such as algorithmic audits, multidisciplinary coordination, regulations for data encryption, and the formation of an AI ethics committee. In addition, this study produces a strategic narrative that can serve as a guide for universities in Indonesia when developing AI systems. The contribution of this study is the creation of a framework that can be applied to provide information to stakeholders on how to align AI-based applications with international standards while remaining oriented towards local values and laws in Indonesia.
Deep learning for mental health analysis: long short-term memory approach to text-based condition classification Zaqqi Yamani; Dinda Lestarini; Sarifah Putri Raflesia; Purwita Sari; Ghita Athalina
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 2: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i2.pp1762-1770

Abstract

The increasing prevalence of mental health disorders highlights the need for scalable and automated approaches to early detection. This study proposes a deep learning–based text classification framework using a long short-term memory (LSTM) network to identify mental health conditions from user generated textual data. A corpus of 103,488 labeled texts representing anxiety, stress, bipolar disorder, depression, personality disorder, suicidal ideation, and normal states was preprocessed through tokenization, padding, and word embedding. The proposed LSTM model achieved overall accuracy of 87% on test set, with strong class-wise performance reflected by precision, recall, and F1-scores, particularly for anxiety, personality disorder, and normal classes. Comparative error analysis using a confusion matrix revealed challenges in distinguishing depression from suicidal ideation, indicating semantic overlap between these conditions. The results demonstrate that LSTM-based models can effectively capture sequential linguistic patterns relevant to mental health classification. This framework shows potential as a decision-support tool for early screening and digital mental health applications, complementing clinical assessment rather than replacing it.
Co-Authors Dinda Lestarini Purwita Sari Sarifah Putri Raflesia Zaqqi Yamani