PENYADARAN BAHAYA UJARAN KEBENCIAN MELALUI #RTIKABDIMAS PROGRAM RELAWAN TEKNOLOGI INFORMASI DAN KOMUNIKASI ABDI MASYARAKAT

Rinda Cahyana, Dewi Tresnawati, Leni Fitriani, Ridwan Setiawan, Eri Satria, Ade Sutedi, Sri Rahayu, Muhammad Rikza Nashrulloh, Rina Kurniawati, Yusnita Habsari Utami

Abstract


Abstrak: Ujaran kebencian merupakan sisi negatif kebebasan berekspresi yang menimbulkan dampak buruk di dunia maya dan dunia nyata. Salah satu cara intervensi ujaran kebencian adalah pembangunan kompetensi literasi digital melalui pendidikan untuk meningkatkan pengetahuan masyarakat akan bahaya ujaran kebencian. Program Relawan Teknologi Informasi dan Komunikasi Abdi Masyarakat yang dikenali di media sosial dengan hastag #RTIKAbdimas adalah program rutin tahunan yang bertujuan untuk melaksanakan upaya pembangunan tersebut di kabupaten Garut. Metode #RTIKAbdimas secara garis besar mencakup perekrutan relawan TIK (Teknologi Informasi dan Komunikasi) dan pelayanan relawan dalam bentuk kegiatan edukasi. Sebanyak 184 orang mahasiswa Teknik Informatika tersebar di 31 kelompok relawan TIK dan menyampaikan layanannya kepada lebih dari 400 remaja di lingkungan mitra yang berada di sejumlah kecamatan dalam lingkup wilayah kabupaten Garut. Rata-rata nilai sertifikasi mereka sebagai relawan TIK adalah 48.56. Hasil survei program kepada mitra menunjukan sekitar 66% kegiatan pelayanan relawan TIK memberikan manfaat pengetahuan, di mana 87% peserta dari mitra merasa puas dan sangat puas. Mitra menilai aspek unggul relawan TIK pada komunikasi dan kerjasama. Menurut hasil tes peserta di awal dan akhir kegiatan, kinerja relawan TIK yang berhasil meningkatkan rata-rata pengetahuan bahaya ujaran kebencian sekitar 5.05 dari 41.12. Berdasarkan skor kinerja individual dan kelompok , sekitar 88% mahasiswa yang berpartisipasi sebagai relawan dalam #RTIKAbdimas terkualifikasi relawan TIK yang unggul.

Abstract: Hate speech is a negative side of freedom of expression that has a harmful impact in cyberspace and the real world. One way of intervening against hate speech is the development of digital literacy competencies through education to increase public knowledge of the dangers of hate speech. The Community Service Information and Communication Technology Volunteer Program, known on social media with the hashtag #RTIKAbdimas is an annual routine program that aims to carry out these development efforts in the Garut district. The #RTIKAbdimas method broadly includes the recruitment of ICT volunteers (Information and Communication Technology) and volunteer services in the form of educational activities. A total of 184 Informatics Information Engineering students are spread across 31 ICT volunteer groups and deliver their services to more than 400 youths in partner environments located in several sub-districts within the Garut district. The average value of their certification as ICT volunteers on duty is 48.56. The results of the program survey to partners show that about 66% of ICT volunteer service activities provide knowledge benefits, of which 87% of participants from partners are satisfied and very satisfied. Partners assess the superior aspects of ICT volunteers in communication and collaboration. According to participants' test results at the beginning and end of the activity, the performance of ICT volunteers who succeeded in increasing the average knowledge of the dangers of hate speech was about 5.05 out of 41.12. Based on individual and group performance scores, about 88% of students who participate as volunteers in #RTIKAbdimas are qualified as excellent ICT volunteers.


Keywords


Digital Literacy; Hate Speech; ICT Volunteers; RTIKAbdimas; Social Media.

Full Text:

DOWNLOAD [PDF]

References


Al-Hassan, A., & Al-Dossari, H. (2019). Detection of hate speech in social networks: a survey on multilingual corpus. 6th International Conference on Computer Science and Information Technology, 10, 10–5121.

Brown, A. (2008). The racial and religious hatred act 2006: a Millian response. Critical Review of International Social and Political Philosophy, 11(1), 1–24.

Cahyana, R., Setiawan, R., Aulawi, H., & Santoso, B. T. (2021). Pembangunan Kompetensi Literasi Digital Sektor Pendidikan Di Masa Pandemi Covid-19 Melalui# RTIKABDIMAS. JMM (Jurnal Masyarakat Mandiri), 5(4), 1606–1617.

Castaño-Pulgarín, S. A., Suárez-Betancur, N., Vega, L. M. T., & López, H. M. H. (2021). Internet, social media and online hate speech. Systematic review. Aggression and Violent Behavior, 58, Issue? Halaman? 101608.

Chetty, N., & Alathur, S. (2018). Hate speech review in the context of online social networks. Aggression and Violent Behavior, 40, Issue? 108–118. https://doi.org/10.1016/J.AVB.2018.05.003

Cohen‐Almagor, R. (2011). Fighting hate and bigotry on the Internet. Policy & Internet, 3(3), 1–26.

Cohen-Almagor, R. (2018). Taking North American white supremacist groups seriously: The scope and the challenge of hate speech on the Internet. International Journal of Crime, Justice, and Social Democracy, 7(2), 38–57.

Ezeibe, C. (2021). Hate speech and election violence in Nigeria. Journal of Asian and African Studies, 56(4), 919–935.

Fino, A. (2020). Defining hate speech: a seemingly elusive task. Journal of International Criminal Justice, 18(1), 31–57.

Fortuna, P., & Nunes, S. (2018). A Survey on Automatic Detection of Hate Speech in Text. ACM Comput. Surv., 51(4). Halaman? https://doi.org/10.1145/3232676

Greenawalt, K. (1996). Fighting words: individuals, communities, and liberties of speech. Tempat Terbit? Princeton University Press.

Kopytowska, M., & Baider, F. (2017). From stereotypes and prejudice to verbal and physical violence: Hate speech in context. Lodz Papers in Pragmatics, 13(2), 133–152.

Law, N., Woo, D., de la Torre, J., & Wong, G. (2018). A global framework of reference on digital literacy skills for indicator 4.4. 2. UNESCO Institute for Statistics (UIS/2018/ICT/IP/51).

Seglow, J. (2016). Hate speech, dignity and self-respect. Ethical Theory and Moral Practice, 19(5), 1103–1116.

Williams, M. L., Burnap, P., & Sloan, L. (2017). Towards an ethical framework for publishing Twitter data in social research: Taking into account users’ views, online context and algorithmic estimation. Sociology, 51(6), 1149–1168.

Zhang, Z., & Luo, L. (2019). Hate speech detection: A solved problem? the challenging case of long tail on twitter. Semantic Web, 10(5), 925–945.




DOI: https://doi.org/10.31764/jmm.v6i5.10121

Refbacks

  • There are currently no refbacks.


Copyright (c) 2022 Rinda Cahyana, Dewi Tresnawati, Leni Fitriani, Ridwan Setiawan, Eri Satria, Ade Sutedi, Sri Rahayu, Muhammad Rikza Nasrulloh, Rina Kurniawati, Yusnita Habsari Utami

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

________________________________________________________________

JMM (Jurnal Masyarakat Mandiri) p-ISSN 2598-8158 & e-ISSN 2614-5758
Email: [email protected]

________________________________________________________________

JMM (Jurnal Masyarakat Mandiri) already indexing:

      

         

 

________________________________________________________________ 

JMM (Jurnal Masyarakat Mandiri) OFFICE: