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Image of TOPIC MODELING MENGGUNAKAN BERTOPIC DENGAN LLAMA2 SEBAGAI TOPIC REPRESENTATION TUNING

Skripsi

TOPIC MODELING MENGGUNAKAN BERTOPIC DENGAN LLAMA2 SEBAGAI TOPIC REPRESENTATION TUNING

Khairi, Alpian - Personal Name;

Penilaian

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Penilaian anda saat ini :  

The growing use of social media, particularly Twitter, has generated large amounts of information in the form of text data covering a wide range of topics and issues. Analyzing Twitter data has the potential to find important insights into topics relevant to society. Topic modeling is one of the latest innovations in text data processing to find topics in a set of text. This research aims to perform topic modeling on Indonesian tweets using BERTopic with LLAMA2 as topic representation tuning. LLAMA2 is used to generate labels from a set of keywords generated from c-TF-IDF calculations. The dataset used consists of 10,000 Indonesian tweets taken from the Twitter account @detikcom. The data is divided into 2 parts, 8,000 tweets are used for training data and 2,000 tweets are used for testing. Based on the results of topic modeling with BERTopic, 49 total topics were obtained. Topic Modeling Evaluation is done using coherence score cv, obtained an average coherence score cv of 0.86 on training data and 0.73 on testing data.


Availability
Inventory Code Barcode Call Number Location Status
2407003248T145486T1454862024Central Library (REFERENCES)Available but not for loan - Not for Loan
Detail Information
Series Title
-
Call Number
T1454862024
Publisher
Indralaya : Fakultas Ilmu Komputer., 2024
Collation
xiii, VI-1 hlm.; ilus.; tab.; 29 cm.
Language
Indonesia
ISBN/ISSN
-
Classification
621.390 7
Content Type
Text
Media Type
unmediated
Carrier Type
unspecified
Edition
-
Subject(s)
Prodi Teknik Informatika
PEMODELAN TOPIK
Specific Detail Info
-
Statement of Responsibility
UIN Farrah
Other version/related

No other version available

File Attachment
  • TOPIC MODELING MENGGUNAKAN BERTOPIC DENGAN LLAMA2 SEBAGAI TOPIC REPRESENTATION TUNING
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