Berliana Septyani Suganda, . (2024) KLASIFIKASI SENTIMEN FENOMENA CHILDFREE PADA KOMENTAR VIDEO YOUTUBE MENGGUNAKAN METODE SUPPORT VECTOR MACHINE (SVM). Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
The use of the internet has become a daily necessity, especially with the increasing use of social media. YouTube, as one of the largest platforms, is a place for users to express opinions about various phenomena, including childfree. In this study, a sentiment analysis of YouTube user comments was conducted to understand people's responses to the childfree phenomenon. It was found that the majority of user sentiment was positive, with a lot of support and encouragement. The Support Vector Machine (SVM) method was used to classify the sentiments, showing significant performance. The use of the oversampling technique SMOTE (Synthetic Minority Over-sampling Technique) helped improve the performance of the model, especially in overcoming class imbalance in the dataset. The evaluation showed an accuracy result of 80% with SMOTE and 79% without SMOTE. This research contributes to understanding people's perception of the social phenomenon of childfree on social media.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No. Panggil: 2010512004] [Pembimbing 1: Ika Nurlaili Isnainiyah] [Pembimbing 2: Ruth Mariana Bunga Wadu] [Penguji 1: Iin Ernawati] [Penguji 2: I Wayan Widi Pradnyana] |
| Uncontrolled Keywords: | Sentiment Analysis, Support Vector Machine, YouTube, Childfree |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General) |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Sistem Informasi (S1) |
| Depositing User: | BERLIANA SEPTYANI SUGANDA |
| Date Deposited: | 11 Sep 2024 01:48 |
| Last Modified: | 11 Sep 2024 01:48 |
| URI: | http://repository.upnvj.ac.id/id/eprint/30526 |
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