Bambang Tri Buwono, . (2022) ANALISIS SENTIMEN PADA MEDIA SOSIAL TWITTER MENGENAI KEBIJAKAN KENAIKAN HARGA BAHAN BAKAR MINYAK MENGGUNAKAN METODE NAIVE BAYES. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
Twitter is a social media to channel or express aspirations, opinions, or shortcomings regarding government policies in making a decision. We can formulate deficiencies or opinions that are channeled by the public through the media on the basis of the objectives contained in the media. In this formulation, steps or procedures are carried out related to the formulation of positive and unfavorable matters regarding the policy of increasing fuel oil prices. We can try the formulation used for the step towards the formulation problem with various methods, one of which is the Naïve Bayes method. We can find the problem of tweet data by using the scraping method. With the formulation of the media, positive and negatif classes are given to make it easier for the formulation to be processed. Media that we can do, namely media tweets also include @KenaikanhargaBBM as a problem formulation. When the media formulation has been presented, the data will be developed into two parts, the 80% training formulation and the 20% test formulation. The end of the formulation has a function, among others, to develop the performance of the methods that have been carried out for accelerating the media to positive and negatif classes, showing the results obtained are 89%.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No.Panggil : 1810511107] [Pembimbing : Nur Hafifah Matondang] [Penguji 1 : Yuni Widiastiwi] [Penguji 2 : Noor Falih] |
| Uncontrolled Keywords: | Tweet, Sentiment Analysis, Naive Bayes, Classification |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
| Depositing User: | Bambang Tri Buwono |
| Date Deposited: | 28 Jul 2022 07:03 |
| Last Modified: | 28 Jul 2022 07:03 |
| URI: | http://repository.upnvj.ac.id/id/eprint/19826 |
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