ANALISIS SENTIMEN TERHADAP PENGGUNA QRIS (QUICK RESPOND CODE INDONESIAN STANDARD) PADA TWITTER MENGGUNAKAN METODE NAÏVE BAYES CLASSIFIER

PARAMITA, PRADIA and Ibrahim, Ali (2023) ANALISIS SENTIMEN TERHADAP PENGGUNA QRIS (QUICK RESPOND CODE INDONESIAN STANDARD) PADA TWITTER MENGGUNAKAN METODE NAÏVE BAYES CLASSIFIER. Undergraduate thesis, Sriwijaya University.

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Abstract

Twitter is currently one of the social media that is widely used by the public. By utilizing Twitter, people can now easily express opinions on various matters, including the Quick Respond Code Indonesian Standard (QRIS). Based on this, an analysis of public sentiment towards QRIS was carried out on social media Twitter using the Naïve Bayes Classifier algorithm. With the aim of finding out whether public sentiment towards QRIS is positive or negative and looking for the level of accuracy of implementing the Naïve Bayes Classifier algorithm. As many as 913 data obtained on Twitter show that public sentiment towards QRIS is 65% positive and 35% negative. Based on the test results on the system, the Naïve Bayes algorithm shows an accuracy of 99.89%, an average precision of 99.83%, and an average recall of 99.68%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Sentiment, Twitter, Naive Bayes
Subjects:	T Technology > T Technology (General) > T1-995 Technology (General)
Divisions:	09-Faculty of Computer Science > 57201-Information Systems (S1)
Depositing User:	Pradia Paramita
Date Deposited:	07 Aug 2023 06:22
Last Modified:	07 Aug 2023 06:22
URI:	http://repository.unsri.ac.id/id/eprint/125900

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