Supriatna, Wahyu Ramdan (2023) ANALISIS SENTIMEN MENGGUNAKAN ALGORITMA NAÏVE BAYES TENTANG REAKSI MASYARAKAT TWITTER TERHADAP KENAIKAN BAHAN BAKAR MINYAK (BBM) TAHUN 2022. Skripsi thesis, Universitas Muhammadiyah Sukabumi.

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Abstract

BBM is a type of fuel that is produced from the bowels of the earth processed in crude oil refineries. Fuel oil is very much needed by the Indonesian people with a large number of population mobility in Indonesia who have means of transportation. world oil caused the government to raise fuel prices, this had a negative impact on society. We can easily see the phenomenon of resistance to fuel price hikes through social media activities, one of which emerges from trending topics on Twitter with the hashtag #BBMnaik. Thus, the tweet data can be used to be processed so as to produce useful information. In the process of carrying out this research through several stages that must be carried out in order to show maximum results. The method used to find out the results of this study is the Naive Bayes method. The tweet data obtained in this study amounted to 1,351 data which will be classified into positive and negative classes. The experimental results used 6 sample documents, 5 as training data and 1 as test data. The probability value that appears in the experiment is 0.000225 which is in P(Positive | Negative) so that the sentiment classification is included in the "Positive" label.

Item Type:	Thesis (Skripsi)
Uncontrolled Keywords:	Twitter, BBM, Sentiment Analysis, Classification, Naïve Bayes
Subjects:	T Technology > T Technology (General)
Divisions:	Fakultas Sains dan Teknologi > Teknik Informatika
Depositing User:	Perpus ID UMMI
Date Deposited:	02 Aug 2023 05:05
Last Modified:	02 Aug 2023 05:05
URI:	http://eprints.ummi.ac.id/id/eprint/3266

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