ANALISIS SENTIMEN TWITTER TERHADAP PERLINDUNGAN DATA PRIBADI DENGAN PENDEKATAN MACHINE LEARNING

Joko Ade Nursiyono(1*), Qorinul Huda(2),

(1) Badan Pusat Statistik Provinsi Jawa Timur
(2) Politeknik Statistika STIS
(*) Corresponding Author

Abstract


As technology and information advances, the main defense and security aspects in the protection of personal data become very important. Protection of personal data is a human right that must be protected by the state. Data digitization is a demand and challenge in the advancement of information. Efforts in protecting personal data are basically carried out through legal certainty instruments in the form of regulations that regulate a system in order to realize a strong system in protecting cyber crime. Various regulations already exist in the legal system in Indonesia. Nevertheless, there are still cases of personal data leakage among Indonesians. The purpose of this study is to describe the condition of personal data protection in Indonesia and analyze cases of data leaks detected in Twitter tweets in the period July 1, 2021 to September 29, 2022. The study was conducted by using Twitter tweet scrapping techniques and classifying netizen responses based on positive, negative, and negative sentiments. neutral. Each sentiment is analyzed with wordcloud by finding what topics are often discussed by netizens on the protection of personal data. Furthermore, the classification evaluation is continued by looking at the accuracy of the machine learning classification algorithm, namely naive bayes and random forest. The results of the study stated that in the period from July 1, 2021 to September 29, 2022, the public's response to the protection of personal data was still negative. Which means that the data protection system in Indonesia is still not effective with the occurrence of various cases of data leakage. Based on the accuracy value, the Naive Bayes algorithm is very good at classifying tweets based on their sentiments, which is 99.84% compared to the random forest algorithm.

Keywords


cyber crime, machine learning, naive bayes, random forest, tweet, twitter.

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References


Admin DPMPTSP Kaltim. (2021). Tanggap Hadapi Insiden Keamanan Siber, Kabid Pengaduan Advokasi dan Informasi Perizinan Hadiri Launching Kaltim-CSIRT Oleh badan Sandi Siber Negara. Retrieved from https://dpmptsp.kaltimprov.go.id/index.php/single-berita/104

Aldean, M. Y., Paradise, P., & Nugraha, N. A. S. (2022). Analisis Sentimen Masyarakat Terhadap Vaksinasi Covid-19 di Twitter Menggunakan Metode Random Forest Classifier (Studi Kasus: Vaksin Sinovac). INISTA: Journal of Informatics, Information System, Software Engineering and Applications, 4(2), 64-72.

Ananda, U. T., Novera, A., Adisti, N. A., & Puispasari, A. (2022). Perlindungan Hukum terhadaop Korban Penyalahgunaan Data Pribadi dalam Pinjaman Online. Repertorium: Jurnal Ilmiah Hukum Kenotariatan, 11(1), 104-113.

Annur, Cindy Mutia. (2022). Kebocoran data Sering Terjadi di 10 Sektor Industri ini. Retrieved from https://databoks.katadata.co.id/datapublish/2022/09/06/kebocoran-data-sering-terjadi-di-10-sektor-industri-ini

Arifah, Dista Amalia. (2011). Kasus Cybercrime Di Indonesia. Jurnal Bisnis dan Ekonomi .Vol. 18 No. 2.

Aswandi, Ririn., dkk. (2020). Perlindungan data dan Informasi Pribadi Melalui Indonesian Data Protection System (IDPS). Lembaga Penalaran dan Penulisan Karya Ilmiah Fakultas Hukum Universitas Hasanuddin. Vol. 3, No. 3, Juni 2020.

CNN Indonesia. (2021). Infografis : Rentetan Kebocoran Data di Indonesia Sejak 2020. Retrieved from https://www.cnnindonesia.com/teknologi/20210523132216-188-645888/infografis-rentetan-kebocoran-data-di-indonesia-sejak-2020

Daffiandra. (2021). Klarifikasi Isu Hoaks 16 November 2021. Retrieved from http://www.beritamagelang.id/hoax/klarifikasi-isu-hoaks-16-november-2021

Delpiero, M., Reynaldi, F. A., Ningdiah, I. U., & Muthmainnah, N. (2021). Analisis Yuridis Kebijakan Privasi dan Pertanggungjawaban Online Marketplace Dalam Perlindungan Data Pribadi Pengguna Pada Kasus Kebocoran Data. Padjadjaran Law Review, 9(1).

KOMINFO. (2016). Indonesia sudah Miliki Aturan soal Perlindungan Data Pribadi. Retrieved from https://www.kominfo.go.id/content/detail/8621/indonesia-sudah-miliki-aturan-soal-perlindungan-data-pribadi/0/sorotan_media

KOMPAS. (2019). Pidato Kenegaraan Presiden Jokowi 2019. Retrieved from https://jeo.kompas.com/naskah-lengkap-pidato-kenegaraan-2019-presiden-jokowi

Nursiyono, Joko Ade. (2021). Pengantar Data Mining dengan R Studio. Binjai: Miranda Novelia.

Pane, A. A., Siregar, F. A., & Sirait, A. S. (2021). Efektivitas Pelaksanaan Silayda E-KTP. Jurnal El-Thawalib, 2(4), 216-225.

Primajaya, A., & Sari, B. N. (2018). Random Forest Algorithm for Prediction of Precipitation. Indonesian Journal of Artificial Intelligence and Data Mining, 1(1), 27. https://doi.org/10.24014/ijaidm.v1i1.4903

Purnama, Bedy. (2019). Pengantar Machine Learning. Bandung: Informatika

Rosalina, S. D., Purbasari, I. Y., & Mandyartha, E. P. (2022). Implementasi Naive Bayes Classifier Untuk Mendiagnosis Penyakit Intellectual Disability. Jurnal Informatika dan Sistem Informasi, 3(2), 115-124.

Sanjaya, B. R., Efrianti, D., Ali, M., Prasetyo, T., Mukhtadi, M., Widasari, Y. K., & Khumairoh, Z. (2022). Pengembangan Cyber Security dalam Menghadapi Cyber Warfare di Indonesia. Journal of Advanced Research in Defense and Security Studies, 1(1), 19-34.

Sanjaya, Bram Ronald., dkk (2022). Pengembangan Cyber Security dalam Menghadapi Cyber Warfare di Indonesia. Journal of Advanced Research in Defense and Security Studies Vol. 1, No. 1, April 200, pp. 19-34.

Sholehurrohman, R., & Ilman, I. S. (2022). Analisis Sentimen Tweet Kasus Kebocoran Data Penggunaan Facebook oleh Cambrigde Analytica. Jurnal Pepadun, 3(1), 140-147.

Undang-Undang Nomor 23 Tahun 2006 Tentang Administrasi Kependudukan pasal 1 ayat 22. Retrieved from: https://peraturan.bpk.go.id/Home/Details/40202.

Undang-Undang Nomor 39 Tahun 1999 tentang Hak Asasi Manusia. Retrieved from: https://peraturan.bpk.go.id/Home/Details/45361/uu-no-39-tahun-1999.

Undang-Undang Dasar Negara RI Tahun 1945 pasal 28G. Retrieved from: https://www.dpr.go.id/jdih/uu1945.

V. W. Siburian and I. E. Mulyana. (2018). Prediksi Harga Ponsel Menggunakan Metode Random Forest, Pros. Annu. Res. Semin., vol. 4, no. 1, pp. 144-147.

Wahyudi Djafar, (2019), Hukum Perlindungan Data Pribadi Di Indonesia: Lanskap,Urgensi, Dan Kebutuhan Pembaharuan, Halaman 5.

Yoga Religia, Agung Nugroho, & Wahyu Hadikristanto. (2021). Klasifikasi Analisis Perbandingan Algoritma Optimasi pada Random Forest untuk Klasifikasi Data Bank Marketing. Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 5(1), 187-192. https://doi.org/10.29207/resti.v5i1.2813




DOI: https://doi.org/10.33172/jpbh.v13i1.1877

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