Afriani, Indah Fatimah (2025) ANALISIS DATA SENTIMEN TERKAIT OPINI HASIL PEMILU 2024 DI MEDIA SOSIAL DENGAN KOMPARASI MODEL KLASIFIKASI TEXT MINING. S1 thesis, Universitas Mercu Buana Jakarta - Menteng.
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Abstract
Dalam era digital, media sosial telah menjadi platform populer bagi masyarakat untuk menyampaikan pendapat mereka tentang pemilu. Penelitian ini bertujuan untuk menganalisis data sentimen terkait opini hasil pemilu 2024 di media sosial dengan menggunakan teknik crawling data. Data opini masyarakat diambil dari platform media sosial seperti Twitter, Facebook, dan Instagram. Penggunaan media sosial di Indonesia meningkat pesat, dengan 167 juta pengguna pada tahun 2023, di mana 153 juta adalah pengguna di atas usia 18 tahun. Instagram menjadi platform yang sangat populer, terutama di kalangan anak muda, yang sering membahas isu politik dan pemilu di sana. Data dikumpulkan menggunakan teknik crawling yang memungkinkan pengambilan data secara otomatis. Pada tahap pra-pemrosesan, dilakukan pembersihan data, penghapusan tautan, penghilangan karakter khusus, dan tokenisasi. Selanjutnya, model klasifikasi text mining seperti Naive Bayes dan Random Forest diterapkan untuk mengklasifikasikan opini masyarakat menjadi tiga kategori sentimen: positif, negatif, dan netral. Hasil analisis menunjukkan bahwa teknik crawling data memungkinkan pengumpulan data opini masyarakat secara efisien dan mendalam dari media sosial. In the digital age, social media has become a popular platform for people to share their opinions about elections. This study aims to analyze sentiment data related to opinions of the 2024 election results on social media using data crawling techniques. Public opinion data is obtained from social media platforms, which include Twitter, Facebook, and Instagram. The use of social media in Indonesia is experiencing very rapid development, launching from data reportal in 2023. There are a total of 167 million social media users, 153 million are users over the age of 18 years, which is 79.5 percent of the total population in Indonesia. Instagram is one of the popular social media with interesting pictures compared to reading. Therefore, Instagram is more in demand, especially by young people, one of which is used to discuss political issues and elections. Data collection is done by utilizing data crawling techniques that allow automatic data retrieval from these platforms. At the data pre-processing stage, steps such as data cleansing, link removal, special character removal, and tokenization are performed to prepare the data before the analysis process. Furthermore, several classification models in text mining, including Naive Bayes and Random Forest methods are applied to classify public opinion into three sentiment categories: positive, negative, and neutral. The results of the analysis show that the use of data crawling techniques allows efficient and in-depth collection of public opinion data from social media.
| Item Type: | Thesis (S1) |
|---|---|
| NIM/NIDN Creators: | 41820120034 |
| Uncontrolled Keywords: | Analisis Sentimen, Opini Masyarakat, Media Sosial, Crawling Data, Text Mining. Sentiment Analysis, Community Opinion, Social Media, Data Crawling, Text Mining |
| 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 > 003 Systems/Sistem-sistem |
| Divisions: | Fakultas Ilmu Komputer > Sistem Informasi |
| Depositing User: | OKTAFIYANI AZ ZAHRO |
| Date Deposited: | 04 Mar 2025 04:30 |
| Last Modified: | 04 Mar 2025 04:30 |
| URI: | http://repository.mercubuana.ac.id/id/eprint/94634 |
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