Rifky, Mochamad Suhri AInur (2023) ANALISIS SENTIMEN PENGGUNA YOUTUBE MENGENAI ANALOG SWITCH OFF (ASO) MENGGUNAKAN WORD EMBEDDING DAN METODE LONG SHORT-TERM MEMORY (LSTM). Undergraduate thesis, UPN Veteran Jawa Timur.
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Abstract
Analog Switch Off (ASO) or migration program from analog television to digital television is a program issued by the Ministry of Communication and Informatics in Indonesia. Some people provide different responses and opinions on YouTube comments about ASO. There are those who give positive or neutral comments. However, there were also those who gave negative comments. Sentiment analysis is a process that is carried out automatically in studying, retrieving, and processing textual data to obtain information and see responses or opinions about an issue or object towards positive, neutral or negative opinions. Thus sentiment analysis can be used as a reference in making organizational decisions, improving a service, or as a review of a product. Sentiment analysis was performed using word embedding with Word2Vec, and sentiment classification using the Long Short-Term Memory (LSTM) method. The results of the validation test were carried out using 168 new data, obtained 63 negative sentiments from 70 data that were true, 52 sentiments were neutral from 57 data that were true, and 59 positive sentiments from 71 data that were true. So the percentage accuracy of the model is 87.78%.
| Item Type: | Thesis (Undergraduate) | ||||||||||||
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| Subjects: | Q Science > QA Mathematics > QA76 Computer software Q Science > QA Mathematics > QA76.6 Computer Programming T Technology > T Technology (General) |
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| Divisions: | Faculty of Computer Science > Departemen of Information Systems | ||||||||||||
| Depositing User: | Mochamad Suhri Ainur Rifky | ||||||||||||
| Date Deposited: | 26 Jul 2023 06:56 | ||||||||||||
| Last Modified: | 26 Jul 2023 06:56 | ||||||||||||
| URI: | http://repository.upnjatim.ac.id/id/eprint/16480 |
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