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Pemodelan Topik Berita Hoax dan Berita Asli Mengenai COVID-19 Menggunakan LDA

GLORIA ELSA AVE C, Ir. Hilya Mudrika Arini, S.T., M.Sc., M.Phil., Ph.D., IPM, ASEAN Eng.; Yun Prihantina Mulyani, S.T., M.Sc., Ph.D, IPM., ASEAN Eng.

2022 | Tesis | MAGISTER TEKNIK INDUSTRI

Saat pandemi banyak ditemukan berita hoax COVID-19. Tingkat popularitas berita hoax dapat membuat pembaca terjebak pada berita hoax karena berita hoax yang diberitakan terus menerus dan topiknya menarik serta unik. Berdasarkan kedua hal tersebut, perlu diketahui topik-topik yang ada di berita hoax. Mengetahui topik pada berita hoax penting sedangkan saat ini belum ada penelitian pemodelan topik berita hoax COVID-19. Penelitian ini akan mencari tahu topik apa saja yang diberitakan pada berita hoax Selain itu pada penelitian ini juga meneliti mengenai topik apa saja yang ada pada berita asli lalu dibandingkan. Mengetahui topik berita asli dan hoax perlu dilakukan untuk menganalisis topik yang dianggap menarik dan banyak diberitakan oleh berita hoax sehingga pihak terkait seperti pemerintah dapat membuat berita asli untuk melawan berita hoax. Data yang digunakan pada penelitian ini yaitu 300 berita asli dan 300 berita yang sudah dikorfirmasi hoax pada situs covid19.go.id. Data diambil pada 28 Juli 2020 sampai 4 April 2021. Pada rentang waktu tersebut, terdapat 300 berita yang dikonfirmasi hoax dan 315 berita asli. Oleh sebab itu seluruh berita yang telah dikonfirmasi hoax digunakan untuk membangun model, sedangkan pada berita asli hanya diambil 300 berita. Pengambilan data berita asli dilakukan secara acak. Design of Experiment yang digunakan dalam penelitian ini adalah Full Factorial Design. Metode yang digunakan dalam penelitian ini adalah Latent Dirichlet Allocation (LDA). Hasil dari penelitian ini yaitu terdapat perbedaan dan persamaan topik pada berita hoax dan berita asli. Ada 10 topik pada berita hoax yaitu Obat dan Cara Untuk Mengatasi Dan Mencegah COVID-19; Internet Fraud Mengenai Bantuan Kuota, Telpon Seluler dan Netflix, Pandangan agama terhadap pandemi; Hoax Global Tentang COVID-19 ; Konspirasi COVID-19 dan Pengaruh Vaksin Dan Protokol Kesehatan Terhadap Tubuh, Program Pemerintah Terkait Ekonomi; Peristiwa yang Menyangkut Public Figure Saat Pandemi; Penggunaan Masker; Vaksin COVID-19 dan Pengumuman Pelaksanaan Protokol Kesehatan. Terdapat 5 topik pada berita asli yaitu Zonasi Wilayah, Perkembangan Penanganan COVID-19 Dan Data Orang Terkonfirmasi COVID-19 Di Suatu Daerah; Pengembangan Vaksin; Pemerataan Vaksinasi dan Fasilitas Kesehatan; Kebijakan Terkait Protokol Kesehatan dan Bantuan Pemerintah Terkait Ekonomi. Implikasi penelitian ini yaitu pemerintah atau pengelola situs covid19.go.id dapat mengetahui apa yang menjadi topik pada berita hoax sehingga dapat menjadi bahan evaluasi terhadap topik-topik berita asli yang mereka terbitkan. Pengelola situs dapat membuat berita dengan topik yang ada pada berita hoax namun belum ada pada berita asli. Pemerintah dapat melawan berita hoax dengan cara banyak menerbitkan berita asli dengan topik berita yang sama pada berita hoax.

During the pandemic, many hoax news about COVID-19 were found. The level of popularity of hoax news can make readers trapped in hoax news because hoax news is reported continuously and the topic is interesting and unique. Based on these two things, it is necessary to familiar the topics of hoax news. Discovering the topic of hoax news is important while currently the modeling research on the topic of hoax news on COVID-19 still lack. This study sought to find out what topics that were reported on hoax news. In addition, this study also examined the topics in the real news and then compared them. Discovering the topic of real and hoax news is conducted to analyze topics that are considered interesting and widely reported by hoax news so related parties such as the government could make real news to fight hoax news. The data used in this study are 300 real news and 300 news that have been confirmed as hoaxes on the covid19.go.id site. Data was taken from July 28, 2020 to April 4, 2021. In that period, there was 300 news confirmed as hoaxes and 315 real news. Therefore, all news that has been confirmed as a hoax is used to build a model, while for real news only 300 pieces of data are taken. Real news data retrieval was taken randomly. The Design of Experiment used in this research is Full Factorial Design. The method used in this research is Latent Dirichlet Allocation (LDA). The results of this study indicated that there were differences and similarities of topics on hoax and real news. The 10 hoax news topics were Medicines and Ways to Overcome and Prevent COVID-19; Internet Fraud Regarding Quota Assistance, Cell Phones and Netflix, Religious views on the pandemic; Global Hoax About COVID-19; The COVID-19 Conspiracy and Effect of Vaccines and Health Protocols on the Body, Internet Fraud Money Assistance Events Relating to Public Figures During a Pandemic; Use of Masks; COVID-19 Vaccine and Health Protocol Implementation Announcement. The 5 real news topics were Regional Zoning, Developments in Handling COVID-19 and Confirmed COVID-19 People Data in an Area; Vaccine Development; Equitable Vaccination and Health Facilities; Patients recover from COVID-19; Policies Related to Health Protocols and Government Assistance Related to the Economy. This research implies that the government or the manager of the covid19.go.id site can find out what is the topic of hoax news so that it can be used as an evaluation for the real news topics they publish. Site managers can create news with topics that are in hoax news but not yet in real news. The government can fight hoax news by publishing lots of real news with the same news topic on hoax news.

Kata Kunci : Pemodelan topik berita, latent dirichlet allocation, topic modeling COVI-19 news, topic modeling fake news, pemodelan topik berita, berita hoax

  1. S2-2022-453210-abstract.pdf  
  2. S2-2022-453210-bibliography.pdf  
  3. S2-2022-453210-tableofcontent.pdf  
  4. S2-2022-453210-title.pdf