PEMODELAN TOPIK PADA TWEET BAHASA INDONESIA MENGGUNAKAN BERTOPIC

DIYASA, FAHMI GUNTARA and Abdiansah, Abdiansah (2023) PEMODELAN TOPIK PADA TWEET BAHASA INDONESIA MENGGUNAKAN BERTOPIC. Undergraduate thesis, Sriwijaya University.

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Abstract

The increasing use of information and communication technology in recent years has had a significant impact on the trend of communicating and expressing aspirations through social media, especially the Twitter platform. Every tweet on Twitter carries information about a particular topic that can be identified through the Topic Modeling method. Topic Modeling is a tool used to uncover hidden topics in a group of documents. This research aims to perform topic modeling on Indonesian tweets using BERTopic. The Topic Modeling process using BERTopic includes steps such as document embedding, dimension reduction with UMAP, document clustering using HDBSCAN, and representing topics using c-TF-IDF. The dataset used consists of 10,000 Indonesian tweets taken from the Twitter account @detikcom. From the 10,000 tweets, 119 main topics and 1 outlier topic were found. Topic Modeling Evaluation is done using coherence score cv, with the average coherence score cv of 0.685, the highest coherence score cv of 0.995, and the lowest coherence score cv of 0.119

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Pemodelan Topik, BERTopic, Cohrence Score cv, Tweet
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Mr Fahmi Guntara Diyasa
Date Deposited:	15 Aug 2023 02:20
Last Modified:	15 Aug 2023 02:20
URI:	http://repository.unsri.ac.id/id/eprint/127188

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