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All Journal Wahana : Tridarma Perguruan Tinggi JIIP (Jurnal Ilmiah Ilmu Pendidikan) Prosiding Konferensi Nasional PKM-CSR Komunita: Jurnal Pengabdian dan Pemberdayaan Masyarakat Jurnal Informatika: Jurnal Pengembangan IT
Primasari, Ina
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Mathematics Nursing Public Health Social Sciences Other

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Journal : Jurnal Informatika: Jurnal Pengembangan IT

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PDF-Document Chatbot Responses using Large Language Models to Enable Smart City Engagement Khadija, Mutiara Auliya; Nurharjadmo, Wahyu; Aziz, Abdul; Primasari, Ina
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 3 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i3.8262

Abstract

Traditional documents, including Rencana Pembangunan Jangka Menengah Daerah (RPJMD), Strategic Plans (Renstra), and e-masterplans, have undergone a remarkable transformation, evolving from their conventional printed formats to the dynamic realm of electronic versions. While this shift holds the promise of enhanced accessibility and convenience for the public, the full potential of these resources remains unrealized due to inherent challenges. On the other hand, a Generative AI approach is employed for the creation of an intelligent chatbot. Our primary contribution lies in the PDF-Document Chatbot Response utilizing Large Language Models (LLMs) GPT 3.5 Turbo from OpenAI, aimed at fostering engagement within Smart City. The dataset consists of Masterplan documents for Smart City development in Yogyakarta City, presented in PDF format and employing the Indonesian language. This research leverages the Large Language Models (LLMs) GPT-3.5 Turbo from OpenAI, in conjunction with user input and prompts. The development process for crafting this chatbot utilizes the LangChain Framework and Pinecone for storing vector embeddings. The results underscore the chatbot's capability to generate coherent responses closely aligned with the context found within the PDF document.
Co-Authors Abdul Aziz Adi Wibowo, Ahimsa Alkhajar , Eka Nada Shofa Anshori, Mahfud Candra Wijaya, Deniawan Tommy Candra, Deniawan Tommy Dwi Tiyanto, Dwi Hans Setyawan Wibowo, Henricus Herwindya Baskara Wijaya, Sri Islamiyah, Hanifah Joko Suranto Khadija, Mutiara Auliya Maditra Permana, Adimas nur amalina, husna Nurharjadmo, Wahyu Permana, Adimas Maditra Prabowo, Henricus Hans Setyawan Puspitasari, Agreianti Setyawan Prabowo, Henricus Hans Shofa Alkhajar, Eka Nada Sri Herwindya Baskara Wijaya, Sri Herwindya Baskara Sulihyantoro, Aryanto Budhy Tommy Candra, Deniawan Tommy Chandra Wijaya, Deniawan Wibowo, Ahimsa Adi