Skripsi

PERBANDINGAN METODE RANDOM FOREST DAN SUPPORT VECTOR MACHINE PADA ANALISIS SENTIMEN FACEBOOK TERHADAP KEMACETAN LALU LINTAS KOTA PALEMBANG

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This research aims to compare the performance of the Random Forest and Support Vector Machine methods in analyzing Facebook data sentiment related to traffic congestion in Palembang City. Data was obtained through a web scraping process and labeled using a lexicon-based approach into three sentiment classes, namely positive, negative, and neutral. Feature representation was performed using the TF-IDF method. The data are then divided into training, validation and testing data. Results showed that the Support Vector Machine produced better performance than Random Forest, particularly in test data. This is due to the suitability of SVM in handling high-dimensional and sparse text data. This research is expected to provide an overview of suitable methods for the analysis of social media sentiment in the context of urban traffic.

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Detail Information

Series Title

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Call Number

T1901232025

Publisher

Indralaya : Prodi Sistem Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2025

Collation

xii, 151 hlm.; ilus.; tab.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

006.312 07

Content Type

Text

Media Type

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Carrier Type

-

Edition

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Subject(s)

Prodi Sistem Komputer
Teknik Pengolahan Data

Specific Detail Info

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Statement of Responsibility

MI

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