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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Saberi, Morteza
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Computer Science & IT Engineering

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Generative Indonesian chatbot for university major selection using transformers embedding Khadija, Mutiara Auliya; Harjito, Bambang; Saberi, Morteza; Paradhita, Astrid Noviana; Nurharjadmo, Wahyu
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 4: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i4.pp3474-3482

Abstract

Selecting a university major is a crucial decision that impacts students' future career paths and personal fulfillment. Traditional guidance methods often lack the personalization and timeliness needed to support students effectively. This study explores the use of Indonesian generative artificial intelligence (AI) chatbots and transformer embeddings to enhance decision-making for university major selection. By leveraging advanced AI techniques, such as bidirectional encoder representations from transformers (BERT) and Gemini embeddings, the research aims to provide personalized, interactive, and contextually relevant guidance. Experiments showed that BERT embeddings achieved the highest accuracy, with recurrent neural network (RNN) and long short-term memory (LSTM) models also performing well but facing issues with overfitting. Gemini embeddings provided strong performance but slightly less effective than BERT. The findings suggest that BERT-based models with RNN are superior for developing decision-support systems in 92% accuracy. Future work should focus on further optimization and integration of user feedback to ensure the relevance and effectiveness of these AI tools in educational settings.
Co-Authors Bambang Harjito, Bambang Khadija, Mutiara Auliya Nurharjadmo, Wahyu Paradhita, Astrid Noviana