Diterbitkan Oleh:
Lembaga Penelitian Pengabdian Masyarakat Universitas Nusa Mandiri
Creation is distributed below Lisensi Creative Commons Atribusi-NonKomersial 4.0 Internasional.
SENTIMENT ANALYSIS ON LGBT ISSUES IN INDONESIA WITH LEXICON-BASED AND SUPPORT VECTOR MACHINE ALGORITHMS
Keywords:
lexicon-based, lgbt, sentiment analysis, support vector machine
Abstract
Non-heterosexual sexual orientation (LGBT) behavior today is one of the most pervasive issues in Indonesian culture. Because of its domino effect on social stability and physical and mental health, the phenomenon known as lesbian, gay, bisexual, and transgender (LGBT) has always been under scrutiny. The development of LGBT people in Indonesia reflects cultural changes that concern many people. Freedom of speech for LGBT people on social media has many public implications. Observation of this phenomenon gives rise to views of anomalies and discrepancies that have drawn criticism. Various attempts have been made to prevent the movement of LGBT people. However, until now, many still debate the pros and cons of this LGBT movement. The lexicon-based method uses a support vector machine to classify public opinion in TikTok video comments about LGBT issues. The lexicon-based method is used as a weighting method, and the support vector machine method is used as a classification method. The results show that the highest gain in sentiment is neutral, with percentage values of 61%, 56%, 68%, 69%, and 63%. The second is positive sentiment, with percentage values of 27%, 27%, 20%, 20%, and 29%. The rest have negative sentiments. With a relatively high accuracy of the five data sets sequentially at 93%, 89%, 95%, 97%, and 91%. This shows that the majority of Indonesians prefer to ignore the issue.
Downloads
Download data is not yet available.
References
Aldinata, Soesanto, A. M., Chandra, V. C., & Suhartono, D. (2023). Sentiments comparison on Twitter about LGBT. Procedia Computer Science, 216, 765–773. https://doi.org/10.1016/j.procs.2022.12.194
Anjani, A. M., Chamid, A. A., & Murti, A. C. (2022). Analisis Sentimen Kaum Lgbt Pada Media Sosial Twitter Menggunakan Algoritma Naïve Bayes. Jurnal Teknik Informatika, 1(2), 1–8. https://doi.org/10.02220/jtinfo.v1i2.259
Annisa, O., & Indrawadi, J. (2020). Peran Pemerintah dalam Menanggulangi LGBT di Kota Payakumbuh. Journal of Civic Education, 3(1), 110–118. https://doi.org/10.24036/jce.v3i1.341
Ardras, D. W., & Voutama, A. (2023). Analisis Sentimen Anti Lgbt Di Indonesia Melalui Media Sosial Twitter. Jurnal Teknika, 15(1), 23–28. https://doi.org/10.30736/jt.v15i1.926
Azmi, K. R. (2020). Student’s LGBT Trend Analysis of Transgender Counseling Through WOCA (Wisdom-Oriented Counseling Approach). Prophetic: Professional, Empathy and Islamic Counseling Journal, 3(1), 25–36. http://dx.doi.org/10.24235/prophetic.v3i1
Cindo, M., & Rini, D. P. (2019). Literatur Review: Metode Klasifikasi Pada Sentimen Analisis. Seminar Nasional Teknologi Komputer & Sains (SAINTEKS), 66–70. Retrieved from https://seminar-id.com/prosiding/index.php/sainteks/article/view/124
Cubernetes. (2023). Functionality [Python]. Retrieved from https://github.com/cubernetes/TikTokCommentScraper (Original work published 2021)
Fitri, V. A., Andreswari, R., & Hasibuan, M. A. (2019). Sentiment Analysis of Social Media Twitter with Case of Anti-LGBT Campaign in Indonesia using Naïve Bayes, Decision Tree, and Random Forest Algorithm. Procedia Computer Science, 161, 765–772. https://doi.org/10.1016/j.procs.2019.11.181
Gawa, E. C. S., & Te’dang, V. (2023). Penggunaan Media Sosial Sebagai Simbol dalam Mendukung Hubungan LGBT. Journal on Education, 05(04), 15598–15608. https://doi.org/10.31004/joe.v5i4.2669
Hasnah, H., & Alang, S. (2019). Lesbian, Gay, Biseksual dan Transgender (Lgbt) Versus Kesehata: Studi Etnografi. Jurnal Kesehatan, 12(1), 63–72. https://doi.org/10.24252/kesehatan.v12i1.9219
Indah R., A., & Susilastuti, D. H. (2020). Different Types Of Stereotype Toward Lgbt As Minority On American Online News. Rubikon : Journal of Transnational American Studies, 7(1), 35–46. https://doi.org/10.22146/rubikon.v7i1.62510
Mahendrajaya, R., Buntoro, G. A., & Setyawan, M. B. (2019). Analisis Sentimen Pengguna Gopay Menggunakan Metode Lexicon Based dan Support Vector Machine. Komputek, 3(2), 52–63. https://doi.org/10.24269/jkt.v3i2.270
Maria, A., & Arief, F. (Directors). (2022). Gerakan Komunitas LGBT di Garut Mulai Mengkhawatirkan | Apa Kabar Indonesia Pagi tvOne. Retrieved from https://www.youtube.com/watch?v=0yvU__KEi6g
Naada, N. (2023). Lima Daerah Di Indonesia Dengan Populasi LGBT Terbanyak. Retrieved March 25, 2023, from Medialokal.co website: https://medialokal.co/news/detail/42644/lima-daerah-di-indonesia-dengan-populasi-lgbt-terbanyak
Oktaviana, N. E., Sari, Y. A., & Indriati, I. (2022). Analisis Sentimen terhadap Kebijakan Kuliah Daring Selama Pandemi Menggunakan Pendekatan Lexicon Based Features dan Support Vector Machine. Jurnal Teknologi Informasi dan Ilmu Komputer, 9(2), 357–362. https://doi.org/10.25126/jtiik.2022925625
Primanita, Y. (2020). Emotional Quotient dan Perilaku Self Injury pada LGBT. Jurnal RAP (Riset Aktual Psikologi Universitas Negeri Padang), 11(1), 90–103. https://doi.org/10.24036/rapun.v11i1.109779
Putu Dian Adnyani. (2022). Problematika Perlindungan Hukum Terhadap Kelompok Lesbian, Gay, Biseksual, dan Transgender (Lgbt) dalam Perspektif Ham Internasional. Ganesha Law Review, 4(1), 35–44. https://doi.org/10.23887/glr.v4i1.1501
Rahmat, U., & Muhammad, R. (2023). Penegasan Bobby Usai Lihat Pasangan Cowok-Cowok: Kota Medan Anti-LGBT. Retrieved March 25, 2023, from Kumparan website: https://kumparan.com/kumparannews/penegasan-bobby-usai-lihat-pasangan-cowok-cowok-kota-medan-anti-lgbt-1zYhTJRUtb9
Romadlon, F. N., Ayuningtyas, G., & Sundayani, R. (2022). The Effect Of Lgbt’s Content In Tik Tok On The Acceptance Of Lgbt By College Students In A Campus Environment. Makna: Jurnal Kajian Komunikasi, Bahasa, Dan Budaya, 10(1), 50–58. https://doi.org/10.33558/makna.v10i1.2494
Sari, I. K., Dewi, R. I. S., & Morika, H. D. (2020). Bahaya Lesbian, Gay, Biseksual, Transgenders (Lgbt) Di Sma Kota Padang. Jurnal Abdimas Saintika, 2(1), 85–90. http://dx.doi.org/10.30633/jas.v2i1.570
Saroh, Y., & Relawati, M. (2017). Indonesian Youth’s Perespective Towards Lgbt. Humanus, 16(1), 71. https://doi.org/10.24036/jh.v16i1.7323
Singgalen, Y. A. (2021). Pemilihan Metode dan Algoritma dalam Analisis Sentimen di Media Sosial: Sistematic Literature Review. Journal of Information Systems and Informatics, 3(2), 278–302. https://doi.org/10.33557/journalisi.v3i2.125
Velando, M. (2020). Analysis of Constitutional Court Decision Number 46/PUU-XIV/2016 Related to LGBT and Community Attitude. Journal of Law and Legal Reform, 1(2), 259–272. https://doi.org/10.15294/jllr.v1i2.35767
Published
2023-03-10
How to Cite
Hoiriyah, H., Qomariya, N., Darmawan, A., Walid, M., & Efenie, Y. (2023). SENTIMENT ANALYSIS ON LGBT ISSUES IN INDONESIA WITH LEXICON-BASED AND SUPPORT VECTOR MACHINE ALGORITHMS. Jurnal Pilar Nusa Mandiri, 19(1), 27-36. https://doi.org/10.33480/pilar.v19i1.4183
Section
Articles
Copyright (c) 2023 Hoiriyah Hoiriyah, Nurul Qomariya, Aang Kisnu Darmawan, Miftahul Walid, Yuri Efenie
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
An author who publishes in the Pilar Nusa Mandiri: Journal of Computing and Information System agrees to the following terms:
- Author retains the copyright and grants the journal the right of first publication of the work simultaneously licensed under the Creative Commons Attribution-NonCommercial 4.0 License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal
- Author is able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book) with the acknowledgement of its initial publication in this journal.
- Author is permitted and encouraged to post his/her work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of the published work (See The Effect of Open Access).
Read more about the Creative Commons Attribution-NonCommercial 4.0 Licence here: https://creativecommons.org/licenses/by-nc/4.0/.
