Analisis Sentimen Opini Masyarakat Terhadap Virus Omicron Di Indonesia Menggunakan Metode Naïve Bayes
DOI:
https://doi.org/10.21111/fij.v7i2.9359Keywords:
Covid-19, Omicron, Media Sosial, Naïve bayesAbstract
AbstrakVirus covid-19 terus bermutasi membentuk varian baru. Varian terakhir yang terdeteksi yaitu, varian Omicron dikenal sebagai varian B.1.1.529. Varian ini pertama kali dilaporkan dari Afrika Selatan pada 24 November 2021 dan saat ini telah menyebar ke seluruh dunia. Pada bulan juli 2022 kasus Omicron mengalami lonjakan. Hal ini menimbulkan banyaknya opini masyarakat khususnya di media sosial mengenai virus omicron. Penelitian ini bertujuan untuk megklasifikasi opini masyarakat terhadap kemunculan virus Omicron pada sosial media twitter dan youtube ke dalam kelas positif, negatif dan netral. Metode yang digunakan pada penelitian ini yaitu algoritma naïve bayes. Naïve bayes merupakan salah satu metode yang bisa digunakan untuk klasifikasi sentiment opini publik. Hasil penelitian sentiment analisis menggunkan naïve bayes menghasilkan tingkat akurasi sebesar 0.82%. Kemudian model diuji untuk membaca opini public di twitter dari tanggal 5 oktober 2022 sampai 27 oktober 2022. Untuk hasil sentiment pengguna twitter pada kata kunci Covid 19 didominasi oleh sentiment positif dengan presentase 85%. Dan untuk sentiment dengan kata kunci Omicron masih didominasi oleh sentiment positif dengan presentase 49%. Disebutkan dari hasil klasifikasi pada data bulan oktober 2022 berarti masyarakat jauh lebih optimis akan menghilangnya virus omicron. Untuk selanjutnya penelitian ini dapat ditingkatkan dengan menambah data atau menggunakan algoritma yang berbeda ataupun implementasi pada algoritma yang sudah ada.Kata kunci: Covid-19, Omicron, Media Sosial, Naïve bayes Abstract[Analysis Of News Sentiment And Public Opinion On Omicron Virus In Indonesia Using The Naïve Bayes Method] The Covid-19 virus continues to mutate to form new variants. The last detected variant, the Omicron variant, is known as the B.1.1.529 variant. This variant was first reported from South Africa on 24 November 2021 and has now spread worldwide. In July 2022 Omicron cases experienced a spike. This has led to a lot of public opinions, especially on social media, about the omicron virus. This study aims to classify public opinion on the emergence of the Omicron virus on Twitter and YouTube social media into positive, negative, and neutral classes. The method used in this study is the naïve Bayes algorithm. Naïve Bayes is a method that can be used to classify public opinion sentiment. The results of sentiment analysis research using naïve Bayes produce an accuracy rate of 0.82%. Then the model was tested to read public opinion on Twitter from 5 October 2022 to 27 October 2022. The results for Twitter user sentiment on the keyword Covid 19 were dominated by positive sentiment with a percentage of 85%. And sentiment with the keyword Omicron is still dominated by positive sentiment with a percentage of 49%. It was stated that the results of the classification of data for October 2022 meant that people were much more optimistic about the disappearance of the Omicron virus. Henceforth this research can be improved by adding data or using a different algorithm or implementing an existing algorithmKeywords: Covid-19, Omicron, Social Media, Naïve BayesReferences
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