SENTIMENT ANALYSIS OF PROGRAM MERDEKA BELAJAR – KAMPUS MERDEKA ON TWITTER USING SUPPORT VECTOR MACHINE
Abstract
Merdeka Belajar - Kampus Merdeka Program as one of the public policies by the Ministry of Education, Culture, Research, and Technology, cannot be separated from public opinion. Opinions are divided into three categories, positive opinions, negative opinions, and neutral opinions. The public expresses opinions through various social media platforms. As a simple social media, Twitter actually has an influence on the process of forming and directing public opinion. Tweet data with the keyword Merdeka Belajar - Kampus Merdeka between August 2020 and February 2021, is used to conduct sentiment analysis to identify the direction of public opinion towards Merdeka Belajar - Kampus Merdeka Program. Sentiment analysis using Support Vector Machine can be applied to predict the direction of a person's sentiment towards the Program Merdeka Belajar – Kampus Merdeka, both positive and negative sentiments. Based on the test results, it can be concluded that the F-measure accuracy value for the positive class is 94.8% and the F-measure accuracy value for the negative class is 95%.
Downloads
References
Prodjo, W.A. (2020, Januari 25). 4 Alasan Nadiem Makarim Mengeluarkan kebijakan kampus Merdeka. Kompas Online. [Online]. Tersedia: https://edukasi.kompas.com/read/2020/01/25/20283891/4-alasan-nadiem-makarim-mengeluarkan-kebijakan-kampus-merdeka.
Irawan, P. (2017). Analisis Opini Publik tentang Kualitas Pelayanan Publik Pemerintah Kota Palembang dalam Rubrik “Lapor Mang Sripo” pada Surat Kabar Sriwijaya Post. [Online]. Tersedia: http://eprints.radenfatah.ac.id/869/1/PURNAMA%20IRAWAN%2012530064%20JURNALISTIK.pdf.
Zaenudin, A. (2018, Maret 21). Bagaimana Twitter Mempengaruhi Opini Publik dan Preferensi Politik. Tirto-id. [Online]. Tersedia: https://tirto.id/bagaimana-twitter-memengaruhi-opini-publik-dan-preferensi-politik-cGre.
Novantirani, A., Sabariah, M.K., Effendy, V., “Analisis Sentimen pada Twitter untuk Mengenai Penggunaan Transportasi Umum Dalam Kota dengan Metode Support Vector Machine,” dalam e-Proceeding of Engineering : Vol.2, No.1 April 2015, hal. 1177.
Dharmapatni, P.M.N., & Merawati, N.L.P. (September, 2020). Penerapan Algoritma Support Vector Machine Dalam Sentimen Analisis Terkait Kenaikan Tarif BPJS Kesehatan. Jurnal BITe. [Online]. Vol 2 No 2. Tersedia: https://journal.universitasbumigora.ac.id/index.php/bite/article/view/904.
Santosa, B. & Umam, A. (2018). Data Mining dan Big Data Analytics. Bantul, Yogyakarta: Penebar Media Pustaka.
DIKTI. (2020). Buku Panduan Merdeka Belajar – Kampus Merdeka. Jakarta: Direktorat Jendral Pendidikan Tinggi Kemdikbud RI.
Aditya, D.B. (2021, Oktober 30). Tantangan dan Harapan FIB dalam Mendukung Merdeka Belajar Kampus Merdeka. Unair News. [Online]. Tersedia: http://news.unair.ac.id/2021/10/30/tantangan-dan-harapan-fib-dalam-mendukung-merdeka-belajar-kampus-merdeka/
MonkeyLearn. (n.d.) Understanding TF-ID: A Simple Introduction. [Online]. Tersedia: https://monkeylearn.com/blog/what-is-tf-idf.
MonkeyLearn. (n.d.) Sentiment Analysis: the Definitive Guide. [Online]. Tersedia: https://monkeylearn.com/sentiment-analysis.
Copyright (c) 2021 Antivirus : Jurnal Ilmiah Teknik Informatika
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Copyright on any article is retained by the author(s).
- Author grant the journal, right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work’s authorship and initial publication in this journal.
- Authors are 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 an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their 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 published work.
- The article and any associated published material is distributed under the Creative Commons Attribution-ShareAlike 4.0 International License
