https://eurogeojournal.eu/ https://jurnal.pendidikanbiologiukaw.ac.id/
https://e-kerja.bnpp.go.id/bkp/https://journal.dkpp.go.id/wow/https://ppid.dkpp.go.id/_fungsi/dana/https://jurnal.pendidikanbiologiukaw.ac.id/https://e-kerja.bnpp.go.id/Pengawas/demo/https://jos.unsoed.ac.id/stats/2024/https://journal.umkendari.ac.id/dm/https://jurnal.radenfatah.ac.id/demo/https://journal.ar-raniry.ac.id/lap/https://sipeg.ui.ac.id/dm/https://e-kerja.bnpp.go.id/Pengawas/dana/
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Analisis Sentimen Warganet Terhadap Keberadaan Juru Parkir Liar Menggunakan Metode Naive Bayes Classifier | Mukti | JURNAL MEDIA INFORMATIKA BUDIDARMA

Analisis Sentimen Warganet Terhadap Keberadaan Juru Parkir Liar Menggunakan Metode Naive Bayes Classifier

Avis Tantra Mukti, Firman Noor Hasan

Abstract


The still high rate of poverty in Indonesia causes many impacts, one of which is the emergence of illegal parking attendants. This condition continues to be supported by the creation of a parking area for business actors for their visitors. The parking areas provided are often free, and even have signs saying so. However, there are individuals who use the free parking space to earn income. There are many netizens' sentiments regarding the phenomenon of lying parking attendants on social media. Therefore, in this research, an analysis was used in the form of netizen sentiment towards illegal parking attendants on social media X using Naïve Bayes. The main objective of this research is to understand the public's feelings towards the existence of illegal parking attendants operating in the parking area. The dataset used in this analysis was 905 taken from social media The results of this research netizens felt very annoyed, angry and disturbed by the presence of illegal parking attendants operating. This is proven by the results of negative sentiment which dominates 93% of the total data or as many as 841 negative sentiments regarding this phenomenon.

Keywords


Sentiment Analysis; Illegal Parking Officer; Social Media X; Tweets; Naïve Bayes Classifier

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DOI: https://doi.org/10.30865/mib.v8i1.6982

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