Implementasi Chatbot Berbasis Large Language Model Untuk Pencarian Skripsi Mahasiswa Terintegrasi dengan Whatsapp

Authors

  • Muhammad Adryan Hasbi Universitas Muhammadiyah Prof Dr Hamka, Indonesia
  • Rahmi Imanda Universitas Muhammadiyah Prof. Dr. HAMKA, Indonesia
  • Muhammad Fathan Fauzan Universitas Muhammadiyah Prof. Dr. HAMKA, Indonesia

DOI:

https://doi.org/10.29240/arcitech.v5i1.13974

Keywords:

Chatbot, LLM, LangChain, WhatsApp, Thesis Search

Abstract

Students often face difficulties in finding relevant thesis references, which can hinder the completion of their final projects and delay graduation. This study aims to develop a chatbot using a Large Language Model (LLM) integrated with WhatsApp as an interactive and efficient solution for academic reference search. A total of 795 classified thesis documents were collected from the Faculty of Industrial Technology and Informatics, UHAMKA. The system was built using the LangChain framework, including Setting Table Schema, Semantic Search, Rank Result, and Natural Language Interface for Databases. Implementation results showed that the chatbot successfully responded to natural language queries with 100% accuracy. User Experience Questionnaire (UEQ) evaluations indicated strong positive responses, with Clarity (2.08) and Accuracy (2.00) achieving “Excellent” ratings indicate high levels of efficiency in conducting thesis searches. This research demonstrates the effective application of LLMs in conversational academic search systems and offers a foundation for the development of similar services in other higher education institutions.

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Author Biographies

Rahmi Imanda, Universitas Muhammadiyah Prof. Dr. HAMKA

Program Studi Teknik Informatika, Fakultas Teknologi Industri dan Informatika

Muhammad Fathan Fauzan, Universitas Muhammadiyah Prof. Dr. HAMKA

Teknik Informatika, Fakultas Industri dan Informatika

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Published

30-06-2025

How to Cite

Hasbi, M. A., Imanda, R., & Fathan Fauzan, M. (2025). Implementasi Chatbot Berbasis Large Language Model Untuk Pencarian Skripsi Mahasiswa Terintegrasi dengan Whatsapp. Arcitech: Journal of Computer Science and Artificial Intelligence, 5(1), 148–167. https://doi.org/10.29240/arcitech.v5i1.13974

Issue

Vol. 5 No. 1 (2025): June 2025

Section

Articles

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Copyright (c) 2025 Muhammad Adryan Hasbi, Rahmi Imanda; Muhammad Fathan Fauzan

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