CHATBOT PENGELOLAAN DATA TERSTRUKTUR DALAM FORMAT CSV MENGGUNAKAN NATURAL LANGUAGE PROCESSING DAN OLLAMA

FASHA, MUSTHAFA KAMAL (2025) CHATBOT PENGELOLAAN DATA TERSTRUKTUR DALAM FORMAT CSV MENGGUNAKAN NATURAL LANGUAGE PROCESSING DAN OLLAMA. S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

In the digital era, managing structured data in CSV format presents significant challenges, particularly for non-technical users. This study aims to develop an Artificial Intelligence (AI)-based chatbot utilizing Natural Language Processing (NLP) methods and the Ollama framework. The chatbot is designed to automatically process CSV data, understand context, and provide relevant responses tailored to user needs. The research methodology involves developing a model based on Ollama and NLP and evaluating its performance using metrics such as accuracy, precision, recall, and F1-score. The results show that the developed chatbot effectively enhances the management of CSV data, delivers accurate responses, and improves user experience in data processing. This study contributes to the advancement of efficient and relevant AI chatbot technology for various applications in business, healthcare, education, and public services. Keywords: Chatbot, Artificial Intelligence, Natural Language Processing, Ollama, Structured Data, CSV Dalam era digital, pengelolaan data terstruktur dalam format CSV menghadirkan tantangan besar, terutama bagi pengguna non-teknis. Penelitian ini bertujuan untuk mengembangkan chatbot berbasis Artificial Intelligence (AI) yang memanfaatkan metode Natural Language Processing (NLP) dan platform Ollama yang mendukung eksekusi lokal model bahasa besar. Chatbot ini dirancang untuk memproses data CSV secara otomatis, memahami konteks, dan memberikan respons yang relevan sesuai kebutuhan pengguna. Metodologi penelitian melibatkan pengembangan model berbasis Ollama dan NLP, serta evaluasi performa menggunakan metrik seperti akurasi, presisi, recall, dan F1-score. Hasil penelitian menunjukkan bahwa chatbot yang dikembangkan mampu meningkatkan efisiensi pengelolaan data CSV, memberikan respons yang akurat, dan memperbaiki pengalaman pengguna dalam mengolah data. Penelitian ini berkontribusi pada pengembangan teknologi chatbot AI yang efisien dan relevan untuk berbagai aplikasi di sektor bisnis, kesehatan, pendidikan, dan layanan publik. Kata kunci: Chatbot, Artificial Intelligence, Natural Language Processing, Ollama, Data Terstruktur, CSV.

Item Type:	Thesis (S1)
Call Number CD:	FIK/INFO. 25 156
NIM/NIDN Creators:	41521010133
Uncontrolled Keywords:	Chatbot, Artificial Intelligence, Natural Language Processing, Ollama, Data Terstruktur, CSV.
Subjects:	000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 006 Special Computer Methods/Metode Komputer Tertentu > 006.3 Artificial Intelligence/Kecerdasan Buatan 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 006 Special Computer Methods/Metode Komputer Tertentu > 006.3 Artificial Intelligence/Kecerdasan Buatan > 006.35 Natural Language Processing/Pengolahan Bahasa Alami
Divisions:	Fakultas Ilmu Komputer > Informatika
Depositing User:	khalimah
Date Deposited:	16 Aug 2025 06:55
Last Modified:	16 Aug 2025 06:55
URI:	http://repository.mercubuana.ac.id/id/eprint/96858

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