Analisis Sentimen Kebijakan Pendidikan di Masa Pandemi COVID-19 dengan CrowdTangle di Instagram

Ahmad Shofwan Afif; Ahmad Raf'ie Pratama

Submitted

5 June 2021

Accepted

26 June 2021

Published

31 August 2021

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PDF Turnitin Similarity Report catatan perbaikan dari reviewer Surat Pernyataan Hak Publikasi

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Abstract

COVID-19 yang ditetapkan sebagai pandemi mengakibatkan banyak negara di dunia menginstruksikan warganya untuk mengadopsi program belajar dari rumah, termasuk di Indonesia. Popularitas media sosial Instagram, terutama di kalangan anak usia sekolah memungkinkannya untuk digunakan sebagai sarana penelitian sentimen publik akan kebijakan pendidikan di masa pandemi ini. Tujuan penelitian ini adalah untuk melihat konten terkait kebijakan pendidikan di masa pandemi seperti apa yang banyak digemari oleh pengguna Instagram di Indonesia, di samping mengkonfirmasi perbedaan pola interaksi audiens dan overperforming score pada konten yang diunggah oleh akun resmi pemerintah jika dibandingkan dengan portal berita, serta berdasarkan tipe konten yang diunggah (Album, IGTV, Photo, Video). Proses analisis data dilakukan secara kualitatif menggunakan word cloud dan pivot table di Power BI serta kuantitatif menggunakan uji statistik t-test dan ANOVA dengan bahasa pemrograman R pada total 74 unggahan yang didapatkan melalui perangkat CrowdTangle dalam rentang waktu satu tahun sejak pandemi ditetapkan. Hasil yang didapatkan menunjukkan bahwa konten tentang pembelajaran tatap muka adalah yang paling digemari oleh pengguna Instagram. Selain itu, terdapat perbedaan fokus konten yang diunggah oleh akun resmi pemerintah dan portal berita. Meski tidak ada perbedaan signifikan pada jumlah interaksi yang didapatkan keduanya, konten yang diunggah oleh portal berita cenderung memiliki overperforming score yang lebih tinggi dibandingkan konten yang diunggah oleh akun resmi pemerintah

Keywords

Analisis Sentimen Instagram Kebijakan Pendidikan Pandemi COVID-19 Akun Resmi Pemerintah Portal Berita

Author Biographies

Ahmad Shofwan Afif, Universitas Islam Indonesia

MAHASISWA S1 INFORMATIKA UNIVERSITAS ISLAM INDONESIA

Ahmad Raf'ie Pratama, Universitas Islam Indonesia

DOSEN S1 INFORMATIKA UNIVERSITAS ISLAM INDONESIA

References

Cucinotta, D., & Vanelli, M. (2020). WHO declares COVID-19 a pandemic. Acta Bio- Medica: Atenei Parmensis, 91(1), 157–160
Bao, Y., Sun, Y., Meng, S., Shi, J., & Lu, L. (2020). 2019-nCoV epidemic: Address mental health care to empower society. The Lancet, 395(10224), e37–e38. https://doi.org/ 10.1016/S0140-6736(20)30309-3
Saleh, A. M. (2020). Problematika Kebijakan Pendidikan Di Tengah Pandemi Dan Dampaknya Terhadap Proses Pembelajaran Di Indonesia. Jurnal Pendidikan, 2(2), 24–24.
C. Longobardi, M. Settanni, M. A. Fabris, dan D. Marengo. (2019). “Follow or be followed: Exploring the links between Instagram popularity, social media addiction, cyber victimization, and subjective happiness in Italian adolescents,” Child. Youth Serv. Rev., vol. 113, no. December 2019, 104955, 2020.
F. Niknam, M. Samadbeik, F. Fatehi, M. Shirdel, M. Rezazadeh, dan P. Bastani. (2020). “COVID-19 on Instagram: A content analysis of selected accounts,” Heal. Policy Technol.
Liu, B., & Zhang, L. (2012). A survey of opinion mining and sentiment analysis. Mining Text Data, 9781461432(3), 415–463. https://doi.org/10.1007/978-1-4614-3223-4_13
Van den Rul, C. (2019). How to Generate Word Clouds in R. towards data science. https://towardsdatascience.com/create-a-word-cloud-with-r-bde3e7422e8a
Pahwa, B., Taruna, S., & Kasliwal, N. (2018). Sentiment Analysis- Strategy for Text Pre-Processing. International Journal of Computer Applications, 180(34), 15–18. https://doi.org/10.5120/ijca2018916865
G.Matt. (2021). How do you calculate overperforming scores?. help.CrowdTangle. https://help.CrowdTangle.com/en/articles/2013937-how-do-you-calculate-overperforming-scores
Niknam, F., Samadbeik, M., Fatehi, F., Shirdel, M., Rezazadeh, M., & Bastani, P. (2020). COVID-19 on Instagram: A content analysis of selected accounts. Health Policy and Technology. https://doi.org/10.1016/j.hlpt.2020.10.016
Yoo, S. Y., Song, J. I., & Jeong, O. R. (2018). Social media contents based sentiment analysis and prediction system. Expert Systems with Applications, 105, 102–111. https://doi.org/10.1016/j.eswa.2018.03.055
Molina, A., Gómez, M., Lyon, A., Aranda, E., & Loibl, W. (2020). What content to post? Evaluating the effectiveness of Facebook communications in destinations. Journal of Destination Marketing and Management, 18(October 2019). https://doi.org/10.1016/j.jdmm.2020.100498
Spillane, T. E., Wong, B. A., & Giovenco, D. P. (2020). Content analysis of Instagram posts by leading cannabis vaporizer brands. Drug and Alcohol Dependence, (October), 108353. https://doi.org/10.1016/j.drugalcdep.2020.108353
S. Derek. Welcome to the CrowdTangle API!. (2021). CrowdTangleHelp, (27 march 2021), https://help.CrowdTangle.com/en/articles/1189612-CrowdTangle-api
R Core Team (2013). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/.
Saleh, A. M. (2020). Problematika Kebijakan Pendidikan Di Tengah Pandemi Dan Dampaknya Terhadap Proses Pembelajaran Di Indonesia. Jurnal Pendidikan, 2(2), 24–24.
Rozi, I., Pramono, S., & Dahlan, E. (2012). Implementasi Opinion Mining (Analisis Sentimen) Untuk Ekstraksi Data Opini Publik Pada Perguruan Tinggi. Jurnal EECCIS, 6(1), 37–43.
Berriche, M., & Altay, S. (2020). Internet users engage more with phatic posts than with health misinformation on Facebook. Palgrave Communications, 6(1), 1–9. https://doi.org/10.1057/s41599-020-0452-1
Poecze, F., Ebster, C., & Strauss, C. (2018). Social media metrics and sentiment analysis to evaluate the effectiveness of social media posts. Procedia Computer Science, 130, 660–666. https://doi.org/10.1016/j.procs.2018.04.117

References

Cucinotta, D., & Vanelli, M. (2020). WHO declares COVID-19 a pandemic. Acta Bio- Medica: Atenei Parmensis, 91(1), 157–160

Bao, Y., Sun, Y., Meng, S., Shi, J., & Lu, L. (2020). 2019-nCoV epidemic: Address mental health care to empower society. The Lancet, 395(10224), e37–e38. https://doi.org/ 10.1016/S0140-6736(20)30309-3

Saleh, A. M. (2020). Problematika Kebijakan Pendidikan Di Tengah Pandemi Dan Dampaknya Terhadap Proses Pembelajaran Di Indonesia. Jurnal Pendidikan, 2(2), 24–24.

C. Longobardi, M. Settanni, M. A. Fabris, dan D. Marengo. (2019). “Follow or be followed: Exploring the links between Instagram popularity, social media addiction, cyber victimization, and subjective happiness in Italian adolescents,” Child. Youth Serv. Rev., vol. 113, no. December 2019, 104955, 2020.

F. Niknam, M. Samadbeik, F. Fatehi, M. Shirdel, M. Rezazadeh, dan P. Bastani. (2020). “COVID-19 on Instagram: A content analysis of selected accounts,” Heal. Policy Technol.

Liu, B., & Zhang, L. (2012). A survey of opinion mining and sentiment analysis. Mining Text Data, 9781461432(3), 415–463. https://doi.org/10.1007/978-1-4614-3223-4_13

Van den Rul, C. (2019). How to Generate Word Clouds in R. towards data science. https://towardsdatascience.com/create-a-word-cloud-with-r-bde3e7422e8a

Pahwa, B., Taruna, S., & Kasliwal, N. (2018). Sentiment Analysis- Strategy for Text Pre-Processing. International Journal of Computer Applications, 180(34), 15–18. https://doi.org/10.5120/ijca2018916865

G.Matt. (2021). How do you calculate overperforming scores?. help.CrowdTangle. https://help.CrowdTangle.com/en/articles/2013937-how-do-you-calculate-overperforming-scores

Niknam, F., Samadbeik, M., Fatehi, F., Shirdel, M., Rezazadeh, M., & Bastani, P. (2020). COVID-19 on Instagram: A content analysis of selected accounts. Health Policy and Technology. https://doi.org/10.1016/j.hlpt.2020.10.016

Yoo, S. Y., Song, J. I., & Jeong, O. R. (2018). Social media contents based sentiment analysis and prediction system. Expert Systems with Applications, 105, 102–111. https://doi.org/10.1016/j.eswa.2018.03.055

Molina, A., Gómez, M., Lyon, A., Aranda, E., & Loibl, W. (2020). What content to post? Evaluating the effectiveness of Facebook communications in destinations. Journal of Destination Marketing and Management, 18(October 2019). https://doi.org/10.1016/j.jdmm.2020.100498

Spillane, T. E., Wong, B. A., & Giovenco, D. P. (2020). Content analysis of Instagram posts by leading cannabis vaporizer brands. Drug and Alcohol Dependence, (October), 108353. https://doi.org/10.1016/j.drugalcdep.2020.108353

S. Derek. Welcome to the CrowdTangle API!. (2021). CrowdTangleHelp, (27 march 2021), https://help.CrowdTangle.com/en/articles/1189612-CrowdTangle-api

R Core Team (2013). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/.

Saleh, A. M. (2020). Problematika Kebijakan Pendidikan Di Tengah Pandemi Dan Dampaknya Terhadap Proses Pembelajaran Di Indonesia. Jurnal Pendidikan, 2(2), 24–24.

Rozi, I., Pramono, S., & Dahlan, E. (2012). Implementasi Opinion Mining (Analisis Sentimen) Untuk Ekstraksi Data Opini Publik Pada Perguruan Tinggi. Jurnal EECCIS, 6(1), 37–43.

Berriche, M., & Altay, S. (2020). Internet users engage more with phatic posts than with health misinformation on Facebook. Palgrave Communications, 6(1), 1–9. https://doi.org/10.1057/s41599-020-0452-1

Poecze, F., Ebster, C., & Strauss, C. (2018). Social media metrics and sentiment analysis to evaluate the effectiveness of social media posts. Procedia Computer Science, 130, 660–666. https://doi.org/10.1016/j.procs.2018.04.117

Analisis Sentimen Kebijakan Pendidikan di Masa Pandemi COVID-19 dengan CrowdTangle di Instagram

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Ahmad Shofwan Afif, Universitas Islam Indonesia

Ahmad Raf'ie Pratama, Universitas Islam Indonesia

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Analisis Sentimen Kebijakan Pendidikan di Masa Pandemi COVID-19 dengan CrowdTangle di Instagram

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Ahmad Shofwan Afif, Universitas Islam Indonesia

Ahmad Raf'ie Pratama, Universitas Islam Indonesia

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