ANALISIS SENTIMEN PENGGUNA APLIKASI TWITTER TERHADAP POLUSI UDARA DI JAKARTA DENGAN MENGGUNAKAN METODE SUPPORT VECTOR MACHINE (SVM)

Rakan Yuvi Ispradityo, . (2024) ANALISIS SENTIMEN PENGGUNA APLIKASI TWITTER TERHADAP POLUSI UDARA DI JAKARTA DENGAN MENGGUNAKAN METODE SUPPORT VECTOR MACHINE (SVM). Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

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Abstract

In this era of advanced technology, social media, especially Twitter, has become one of the main platforms for voicing opinions and social issues. One issue that is often discussed on Twitter is air pollution in Jakarta, which is considered one of the biggest environmental problems in the city. This study aims to analyze the sentiment of Twitter users towards air pollution in Jakarta using the Support Vector Machine (SVM) method. The data used in this study comes from 2022 Indonesian tweets collected from September 2023 to August 2024. Pre-processing is done to clean and prepare the data, then sentiment labeling is done to be positive or negative. SVM method with linear kernel was used to predict sentiment, with random division of training and test data. The results showed that negative sentiment dominated, with 1884 tweets with negative sentiment and 111 tweets with positive sentiment. This study confirms that SVM performs well in sentiment classification, and air pollution in Jakarta is a topic that has received significant attention from the public. Keywords : Twitter, air pollution, Jakarta, sentiment analysis, Support Vector Machine (SVM), social media, data pre-processing, sentiment classification.

Item Type: Thesis (Skripsi)
Additional Information: [No. Panggil: 2010512104] [Pembimbing 1: Ruth Mariana Bunga Wadu] [Pembimbing 2: Bambang Tri Wahyono] [Penguji 1: Ati Zaidiah] [Penguji 2: Nindy Irzavika]
Uncontrolled Keywords: Twitter, Air Pollution, Jakarta, Sentiment Analysis, Support Vector Machine (SVM), Social Media, Data Pre-Processing, Sentiment Classification.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions: Fakultas Ilmu Komputer > Program Studi Sistem Informasi (S1)
Depositing User: RAKAN YUVI ISPRADITYO
Date Deposited: 24 Mar 2025 01:37
Last Modified: 24 Mar 2025 01:37
URI: http://repository.upnvj.ac.id/id/eprint/34844

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