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Implementasi Text Mining Dengan Random Forest Untuk Analisa Sentimen Tanggapan Masyarakat Di Twitter Terhadap RKUHP 2022

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dc.contributor.author Liswandi, Hendra
dc.date.accessioned 2023-07-25T04:08:36Z
dc.date.available 2023-07-25T04:08:36Z
dc.date.issued 2023-05
dc.identifier.citation Perpustakaan en_US
dc.identifier.other Elfitra
dc.identifier.uri https://repository.unri.ac.id/handle/123456789/11065
dc.description.abstract Indonesia is a state of the law as stipulated in Article 1 paragraph (3) of the third amendment of the 1945 Constitution. The state sets rules and policies to regulate society. The power exercised by the government/ruler can be interpreted as state action. This includes the enactment of the Criminal Code, commonly known as the Criminal Code, which is confirmed by Law Number 73 of 1958 concerning the enactment of Law Number 1 of 1946 of the Republic of Indonesia concerning criminal law regulations for the entired territory of the Republic of Indonesia and amending the Criminal Code. The Draft Criminal Code (RKUHP), which has not yet been ratified, has drawn a lot of criticism in Indonesia because it is considered over criminalization. The amount of criticism conveyed by the public has caused the RKUHP to become one of the trending topics or the most frequently discussed topics in 2022. The Draft Criminal Code will be passed in July 2022 by the government and the House of Representatives. One of the articles that are being discussed by the public is the punishment for people who insult the government, especially on social media. Some people think that the article deviates from Indonesia's democratic system. With the advancement of technology, many people complain about the changes in the Criminal Code on social media, especially Twitter. Therefore, the researcher aimed to determine the accuracy of the results of public sentiment toward the 2022 Criminal Code on Twitter used the Random Forest method. In this study, data collection used a snsscraper in jupyter notebook. The data used was data from October 2022 to November 2022. This method produced the highest accuracy of 0.81 at the 7th index and the lowest accuracy is 0.61 at the 4th index. en_US
dc.description.provenance Submitted by wahyu sari yeni (ayoe32@ymail.com) on 2023-07-25T04:08:36Z No. of bitstreams: 1 Hendra Liswandi_compressed.pdf: 251905 bytes, checksum: 6d0886f206bda4347be70bfc6131821e (MD5) en
dc.description.provenance Made available in DSpace on 2023-07-25T04:08:36Z (GMT). No. of bitstreams: 1 Hendra Liswandi_compressed.pdf: 251905 bytes, checksum: 6d0886f206bda4347be70bfc6131821e (MD5) Previous issue date: 2023-05 en
dc.description.sponsorship Fakultas Matematika dan Ilmu Pengetahuan Alam en_US
dc.language.iso en en_US
dc.publisher Elfitra en_US
dc.subject Sentiment Analysis en_US
dc.subject RKUHP en_US
dc.subject Random Forest en_US
dc.title Implementasi Text Mining Dengan Random Forest Untuk Analisa Sentimen Tanggapan Masyarakat Di Twitter Terhadap RKUHP 2022 en_US
dc.type Article en_US
dc.contributor.supervisor Aminuddin, Al


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