Alya Zahra Waty, . (2024) ANALISIS SENTIMEN RESPONS PUBLIK PADA MEDIA SOSIAL X TERHADAP PENGESAHAN UNDANG-UNDANG KESEHATAN DI INDONESIA MENGGUNAKAN METODE NAÏVE BAYES. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
On July 11, 2023, the Draft Health Law was passed by the Indonesian House of Representatives (DPR). This law contains provisions that support the implementation of health transformation, such as strengthening disease prevention efforts, enhancing patient-centered healthcare services, and reaching communities through healthcare units in villages. However, during its enactment process, a variety of responses and reactions emerged from the public. Social Media X is one of the platforms used to express opinions and discuss controversial issues, such as the passage of the Health Law. The abundance of opinions on Social Media X has made it difficult to understand the public's sentiment regarding the enactment of the Health Law. Based on this issue, a study was conducted to analyze the sentiment of public responses on Social Media X regarding the enactment of the Health Law using the Naive Bayes method. The study involved collecting data from Social Media X and manually labeling it as either positive or negative sentiment by three annotators. The data was then preprocessed, weighted using TF-IDF, divided into 80% training data and 20% test data, and modeled using the Naive Bayes algorithm. The evaluation results showed an accuracy of 81%, precision of 88%, recall of 42%, and an F1-Score of 57%. Additionally, an analysis of the classification results was performed through visualization using Tableau Public. The study provides insights, revealing that the majority of Social Media X users responded negatively to the enactment of the Health Law, and based on the visualization conducted, it is suggested that the government reconsider the enacted law.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No.Panggil: 2010512065] [Pembimbing: Nur Hafifah Matondang, S.Kom., M.M., M.T.I.] [Penguji 1: Ruth Mariana Bunga Wadu, S.Kom., M.M.S.I.] [Penguji 2: Bambang Triwahyono, S.Kom., M.Si.] |
| Uncontrolled Keywords: | Sentiment Analysis, X, Health Bill, Naive Bayes, Tableau Public |
| 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: | ALYA ZAHRA WATY |
| Date Deposited: | 26 Jul 2024 06:05 |
| Last Modified: | 24 Sep 2024 06:40 |
| URI: | http://repository.upnvj.ac.id/id/eprint/30821 |
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