Aprilia, Salma Dian (2024) Klasifikasi Berita Hoax Konflik Palestina-Israel Menggunakan Multinomial Naïve Bayes dengan Optimasi Particle Swarm Optimization. Undergraduate thesis, UPN Veteran Jawa Timur.
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Abstract
News has an important position as a source of information in society. The development of the digitalization era also supports the emergence of online news portals. From the initial news only in print media, radio or television, at this time news can be disseminated through social media, including by disseminating through online news websites. With the increasingly open access to information dissemination, there are many cases of hoax news dissemination whose truth cannot be proven. The topic that is currently being discussed is the Palestinian-Israeli conflict. To make a hoax news classification, an algorithm is needed that supports this. The algorithm is Multinomial Naïve Bayes which is effective in text classification. To make the resulting accuracy rate higher, an optimization method is added, namely Particle Swarm Optimization which acts as a hyperparameter tuning in this study. The test results show that the classification experiment with the Multinomial Naïve Bayes algorithm produces the highest accuracy with a data division of 90%:10%, which is 76%, while the experiment with the addition of Particle Swarm Optimization with a data division of 90%:10%, the accuracy rate increases to 84%. This proves that the Particle Swarm Optimization optimization method is capable of increasing the accuracy rate results.
| Item Type: | Thesis (Undergraduate) | ||||||||||||
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| Subjects: | T Technology > T Technology (General) | ||||||||||||
| Divisions: | Faculty of Computer Science > Departemen of Informatics | ||||||||||||
| Depositing User: | Salma Dian Aprilia | ||||||||||||
| Date Deposited: | 04 Jun 2024 02:46 | ||||||||||||
| Last Modified: | 04 Jun 2024 02:46 | ||||||||||||
| URI: | https://repository.upnjatim.ac.id/id/eprint/23671 |
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