Perbandingan Kinerja Naïve Bayes dan Random Forest dalam Mendeteksi Berita Palsu
Fake news has become a serious problem in today's digital era. The existence of fake news can have various negative impacts, including the spread of misinformation, social unrest, and economic losses. This study compares the performance of Naïve Bayes and Random Forest classification methods i...
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| Format: | Article |
| Language: | English |
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Universitas Islam Negeri Sunan Kalijaga Yogyakarta
2025-05-01
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| Series: | JISKA (Jurnal Informatika Sunan Kalijaga) |
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| Online Access: | https://ejournal.uin-suka.ac.id/saintek/JISKA/article/view/4336 |
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| author | William William Teny Handhayani |
| author_facet | William William Teny Handhayani |
| author_sort | William William |
| collection | DOAJ |
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Fake news has become a serious problem in today's digital era. The existence of fake news can have various negative impacts, including the spread of misinformation, social unrest, and economic losses. This study compares the performance of Naïve Bayes and Random Forest classification methods in detecting fake news. Both methods were evaluated on a news dataset comprising 44,898 samples. It uses public data from the Kaggle repository. The news samples are represented by four features: title, news content, subject, and news date. This data is then subjected to cleaning, stemming, tokenization, and feature extraction. The results indicate that the Random Forest method outperforms the Naïve Bayes method. The Random Forest method has an accuracy of 99%, while the Naïve Bayes method has an accuracy of 96%. In general, this research demonstrates that the Random Forest method can be a viable alternative for detecting fake news.
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| format | Article |
| id | doaj-art-0249d0620ec84d3d9232d29facd7bb39 |
| institution | DOAJ |
| issn | 2527-5836 2528-0074 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Universitas Islam Negeri Sunan Kalijaga Yogyakarta |
| record_format | Article |
| series | JISKA (Jurnal Informatika Sunan Kalijaga) |
| spelling | doaj-art-0249d0620ec84d3d9232d29facd7bb392025-08-20T03:07:28ZengUniversitas Islam Negeri Sunan Kalijaga YogyakartaJISKA (Jurnal Informatika Sunan Kalijaga)2527-58362528-00742025-05-01102Perbandingan Kinerja Naïve Bayes dan Random Forest dalam Mendeteksi Berita PalsuWilliam William0Teny Handhayani1Universitas TarumanagaraUniversitas Tarumanagara Fake news has become a serious problem in today's digital era. The existence of fake news can have various negative impacts, including the spread of misinformation, social unrest, and economic losses. This study compares the performance of Naïve Bayes and Random Forest classification methods in detecting fake news. Both methods were evaluated on a news dataset comprising 44,898 samples. It uses public data from the Kaggle repository. The news samples are represented by four features: title, news content, subject, and news date. This data is then subjected to cleaning, stemming, tokenization, and feature extraction. The results indicate that the Random Forest method outperforms the Naïve Bayes method. The Random Forest method has an accuracy of 99%, while the Naïve Bayes method has an accuracy of 96%. In general, this research demonstrates that the Random Forest method can be a viable alternative for detecting fake news. https://ejournal.uin-suka.ac.id/saintek/JISKA/article/view/4336Random ForestNaive Bayes AlgorithmText ClassificationFake News DetectionMachine Learning |
| spellingShingle | William William Teny Handhayani Perbandingan Kinerja Naïve Bayes dan Random Forest dalam Mendeteksi Berita Palsu JISKA (Jurnal Informatika Sunan Kalijaga) Random Forest Naive Bayes Algorithm Text Classification Fake News Detection Machine Learning |
| title | Perbandingan Kinerja Naïve Bayes dan Random Forest dalam Mendeteksi Berita Palsu |
| title_full | Perbandingan Kinerja Naïve Bayes dan Random Forest dalam Mendeteksi Berita Palsu |
| title_fullStr | Perbandingan Kinerja Naïve Bayes dan Random Forest dalam Mendeteksi Berita Palsu |
| title_full_unstemmed | Perbandingan Kinerja Naïve Bayes dan Random Forest dalam Mendeteksi Berita Palsu |
| title_short | Perbandingan Kinerja Naïve Bayes dan Random Forest dalam Mendeteksi Berita Palsu |
| title_sort | perbandingan kinerja naive bayes dan random forest dalam mendeteksi berita palsu |
| topic | Random Forest Naive Bayes Algorithm Text Classification Fake News Detection Machine Learning |
| url | https://ejournal.uin-suka.ac.id/saintek/JISKA/article/view/4336 |
| work_keys_str_mv | AT williamwilliam perbandingankinerjanaivebayesdanrandomforestdalammendeteksiberitapalsu AT tenyhandhayani perbandingankinerjanaivebayesdanrandomforestdalammendeteksiberitapalsu |