Vilya Lakstian Catra Mulia
Politeknik Harapan Bangsa Surakarta

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MEMBANGUN KEPERCAYAAN PUBLIK UNTUK MEMULAI PROGRAM VAKSINASI COVID-19 DI INDONESIA: ANALISIS MULTIMODAL KEBAHASAAN Vilya Lakstian Catra Mulia
Widyaparwa Vol 50, No 2 (2022)
Publisher : Balai Bahasa Provinsi Daerah Istimewa Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (328.389 KB) | DOI: 10.26499/wdprw.v50i2.982

Abstract

The discovery of Covid-19 vaccine gives opportunity to people for getting better immunity. However in its presence, Covid-19 vaccine is faced with some worries about its contents. The Indonesian Ministry of Religious Affairs and The Ministry of Health had role in constructing people’s belief towards the vaccine’s safety and halal so that vaccination program would be done soon. Various ways were applied, including using social media. Through this research, the researcher collected the data from the data source in the form of multimodal documents which were from the official accounts by the Ministry of Religious Affairs and Health in Facebook for socializing the first Covid-19 vaccine received by Indonesia, Sinovac. The research was done by linguistic multimodal analysis along with Systemic Functional Linguistics (SFL) and social photography approaches. The collected data had fulfilled the criteria formulated by the researcher. Using interpersonal and textual analysis with SFL, the researcher discusses how socialization applied by those two ministries implementing texts for building relation between the ministries and practicing communication strategy. Supported by social photography analysis, constructing belief visually is formed from the findings of subject’s position, eye contact, and camera shot. This research finally does not only give scientific study of language, but also connect it with the technique of implementing visual communication.Ditemukannya vaksin Covid-19 memberikan peluang kepada masyarakat untuk memperoleh imunitas yang lebih baik. Namun, di awal penemuannya, vaksin Covid-19 dihadapkan pada sejumlah keraguan atas kandungannya. Kementerian Agama (Kemenag) dan Kementerian Kesehatan (Kemenkes) Republik Indonesia berperan besar dalam membangun kepercayaan publik terhadap keamanan dan kehalalannya sehingga program vaksinasi dapat segera dilakukan. Beragam cara dilakukan termasuk melalui media sosial. Melalui penelitian ini, peneliti mengumpulkan data dari sumber data dokumen multimodal, yaitu postingan visual dari akun resmi Kemenag dan Kemenkes di Facebook dalam menyosialisasikan vaksin Covid-19 pertama yang diterima Indonesia, Sinovac. Penelitian dilakukan dengan analisis multimodal kebahasaan dengan pendekatan Linguistik Sistemik Fungsional (LSF) dan fotografi sosial. Data yang diperoleh telah memenuhi kriteria yang diformulasikan oleh peneliti. Melalui analisis makna interpersonal dan tekstual dengan LSF, peneliti membahas bagaimana sosialiasi yang dilakukan Kemenag dan Kemenkes  mengimplementasikan teks untuk membangun relasi antarkedua lembaga tersebut dan strategi komunikasi yang dijalankan. Dengan dukungan analisis fotografi sosial, membangun kepercayaan secara visual dibentuk dari hasil posisi subjek, kontak mata, serta bidikan kamera. Penelitian ini akhirnya tidak hanya memberikan kajian ilmiah terhadap bahasa saja, tetapi juga mengaitkannya dengan teknik kerja komunikasi visual
LANGUAGE ATTITUDE AND SENTIMENT ANALYSES IN GETTING THE INSIGHTS TOWARDS COVID-19’S OMICRON VARIANT NEWS Vilya Lakstian Catra Mulia; Chairullah Naury; Ika Purnamasari; Libel Meiliana
Mahakarya: Jurnal Mahasiswa Ilmu Budaya Vol. 4 No. 1 (2023)
Publisher : IAIN Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22515/msjcs.v4i1.6613

Abstract

Omicron variant has been massively reported on Indonesian mass media following the spread of other previous variants during Covid-19 pandemic. This research combines computer science and linguistics to analyze the news on the variant. It implemented quantitative research using computational algorithm by collecting the titles of the news from Indonesian mainstream online mass media. Sentiment Analysis (SA) was applied to obtain the sentiments, opinion, and subjectivities of the texts along with topic modeling in classifying the topics. The words in the headline news titles were used as the data and grabbed by Python programming language. A criterion-based sampling was employed in to select the relevant data and to formulate the criteria in the research methodology. The results were filtered to ‘Omicron’ keyword for SA processing by the Azure Text Sentiment Analysis tool. The results of SA, as computational research, was then confirmed with Attitude Analysis (AA) from the perspective of Systemic Functional Linguistics. AA classified the words into affect, judgment, and appreciation as the attitude construed in English text. This research provides SA as the insights of Omicron issue. The presence of AA extracts the words into bipolar senses of human’s meaning interpretation. AA is important to straighten SA findings. SA has contextual meaning problem and requires study on its words classified in ‘neutral’ which are then confidently directed into positive or negative meanings by AA. It is found that there are different dynamics by SA and AA findings as they reflect particular meanings. Besides their difference, SA is useful for managing overload data into fast policy making whereas AA makes sure the acceptable meanings to people. In this case AA corrects the bias occurring from SA.