Implementasi Retrieval Augmented Generation dan Dynamic Topic Modeling untuk Smart Assistant Berbasis Web
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Graciella Eunike Bawiling
*
Politeknik Negeri Manado, Manado,
Indonesia
- Fify Mustika Wondal Politeknik Negeri Manado, Manado, Indonesia
- Maksy Sendiang Politeknik Negeri Manado, Manado, Indonesia
- Tracy Kereh Politeknik Negeri Manado, Manado, Indonesia (*) Corresponding Author
Abstract
Center for research and Community Service (P3M) Politeknik Negeri Manado faces challenges in providing information services that are fast, accurate, and relevant to the academic community. The research title consultation process is still carried out manually and has not been supported by a system that is able to map the latest research trends to provide prospective research topic recommendations. This condition has the potential to cause delays in information and lack of updates on global research developments for lecturers and students. This study aims to develop a web-based Smart Assistant feature that is able to automate P3M information services while providing research title recommendations based on research Trend Analysis. The system was developed by integrating two Artificial Intelligence methods, namely Retrieval Augmented Generation (RAG) to generate chatbot answers based on P3M internal documents and external data through APIs, and Dynamic Topic Modeling using a topical algorithm to analyze research title trends from scientific publication data. The results of the study in the form of Smart Assistant features P3M Manado State Polytechnic, which provides interactive conversation Services and research title recommendations. This system is expected to improve the efficiency of administrative services and help lecturers and students in determining relevant research topics and based on the latest data.
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