Analisis Sentimen Pro dan Kontra Masyarakat Indonesia tentang Vaksin COVID-19 pada Media Sosial Twitter

Fajar Fathur Rachman, Setia Pramana

Abstract


Abstract

In order to accelerate the handling of the spread of COVID-19 in Indonesia, the Government of the Republic of Indonesia has issued a discourse on vaccination for the Indonesian people at the end of 2020. Although the government has not officially released the schedule or procedure for the vaccinations, the discourse is considered controversial so that it has invited many groups of people to give their opinions in various media. This opinion must be considered as material for evaluation so that the vaccination discourse that will be carried out can run well. By utilizing data from social media twitter, this study aims to analyze the public's response to the vaccination discourse by classifying these responses into positive and negative responses. Furthermore, there will also be grouping of public opinion using the Latent Dirichlet Allocation (LDA) method to find out what topics of conversation are often discussed by the community regarding the vaccination discourse. The results of the analysis show that the public gives more positive responses to the discourse (30%) than the negative responses (26%). The words with the most frequent appearances also indicate that there are more words with a positive sentiment than the words with a negative sentiment. The LDA model that was built can also capture the topics discussed by the community regarding the vaccination discourse, such as public talks about vaccine controversies which are considered hasty, halal certification of vaccines and public doubts about the quality of the vaccine to be used.

Keyword: COVID-19, Latent Dirichlet Allocation (LDA), sentiment analysis, twitter, vaccine

Abstrak

Dalam rangka melakukan percepatan penanganan penyebaran COVID-19 di Indonesia, Pemerintah Republik Indonesia telah mengeluarkan wacana vaksinasi untuk masyarakat Indonesia pada akhir tahun 2020 mendatang. Meskipun pemerintah belum secara resmi merilis jadwal maupun prosedur vaksinasi yang akan dilakukan, wacana tersebut dinilai kontroversial sehingga mengundang banyak kalangan untuk memberikan pendapatnya di berbagai media. Pendapat tersebut haruslah dipertimbangkan sebagai bahan evaluasi sehingga rencana vaksinasi yang akan dilakukan dapat berjalan dengan baik. Dengan memanfaatkan data dari media sosial twitter, penelitian ini bertujuan untuk menganalisis respon masyarakat terhadap wacana vaksinasi dengan cara mengklasifikasikan respon tersebut ke dalam respon positif dan negatif. Selanjutnya juga akan dilakukan pengelompokkan opini masyarakat menggunakan metode Latent Dirichlet Allocation (LDA) untuk mengetahui topik pembicaraan yang sering dibahas oleh masyarakat terkait dengan wacana vaksinasi tersebut. Hasil analisis menunjukkan bahwa masyarakat lebih banyak memberikan respon positif terhadap wacana tersebut (30%) dibandingkan dengan respon negatifnya (26%). Kata-kata bersentimen yang paling sering muncul juga mengindikasikan lebih banyak kata yang bersentimen positif dibandingkan dengan kata yang bersentimen negatif. Model LDA yang dibangun juga dapat menangkap topik yang dibicarakan masyarakat terkait wacana vaksinasi tersebut seperti pembicaraan masyarakat mengenai kontroversi vaksin yang dinilai terburu-buru, sertifikasi halal vaksin dan keraguan masyarakat terhadap kualitas vaksin yang akan digunakan.

Kata Kunci: COVID-19, vaksin, analisis sentimen, Latent Dirichlet Allocation, twitter

 


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