Analisis Sentimen Terhadap KPU 2024 Berdasarkan Tweet Media Sosial Twitter Menggunakan Algoritma Naïve Bayes
DOI:
https://doi.org/10.30865/klik.v4i4.1587Keywords:
Setiment Analysis; KPU 2024; Twitter; Rapidminer; Naïve BayesAbstract
The development of technology is currently very rapid making the dissemination of information faster, the dissemination of information is very easy to get on social media such as Twitter. Twitter social media itself provides features for its users to be able to send and read information in the form of text or video. Elections are a very important moment for the Indonesian people in choosing leaders, in this case the "2024 KPU" as the organizer is expected to be able to run the elections so that they run well. Twitter data collected with the keyword "KPU 2024" obtained a total of 3057 datasets, followed by a cleansing process which produced 715 datasets. The aim of this research is to find out how many positive and negative tweets comments and to indicate the accuracy of the implementation of the Naïve Bayes method. The accuracy results given by the Naïve Bayes algorithm are 67.13% with a precision of 66.04% and a recall of 100.00%. This research was conducted to see public sentiment towards the "2024 KPU" later. Evaluation results in the confusion matrix obtained true positives of 457 and true negatives of 235
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References
D. Darwis, N. Siskawati, and Z. Abidin, “Penerapan Algoritma Naive Bayes Untuk Analisis Sentimen Review Data Twitter Bmkg Nasional,” J. Tekno Kompak, vol. 15, no. 1, p. 131, 2021, doi: 10.33365/jtk.v15i1.744.
A. Rahma and S. Delliana, “Pengaruh Konten Youtube Ria Ricis Terhadap Agresi Verbal Netizen,” Translitera J. Kaji. …, vol. 11, no. 1, pp. 106–119, 2022, doi: https://doi.org/10.35457/translitera.v11i1.1668.
A. R. Abdillah, F. N. Hasan, T. Informatika, F. N. Hasan, D. Mining, and A. Sentimen, “Analisis Sentimen Terhadap Kandidat Calon Presiden Berdasarkan Tweets Di Sosial Media Menggunakan Naive Bayes Classifier Sentiment Analysis of Presidential Candidates Based on Tweets on,” vol. 13, no. 1, pp. 117–130, 2023, doi: https://doi.org/10.32664/smatika.v13i01.750.
W. Maulana and M. Mulyadi, “Ujaran Kebencian Terhadap Jokowi pada Masa Pandemi Covid-19: Studi Kasus Twitter,” J. Lisnguistik Komputasional, vol. 4, no. 1, pp. 27–33, 2021, doi: https://doi.org/10.26418/jlk.v4i1.42.
A. R. Alifvia, U. Saprudin, K. Metro, and R. Miner, “ANALISIS SENTIMEN REVIEW DATA TWITTER KOMISI PEMILIHAN UMUM ( KPU ) MENGGUNAKAN METODE NAÏVE BAYES,” vol. 11, no. 1, pp. 81–84, 2023, doi: https://doi.org/10.35959/jik.v11i01.407.
B. J. Yuri, A. Zetra, and R. E. Putera, “Analisis Kebijakan KPU dalam Rekrutmen KPPS untuk Pemilu 2024,” SOSIOHUMANIORA J. Ilm. Ilmu Sos. Dan Hum., vol. 9, no. 1, pp. 145–154, 2023, doi: 10.30738/sosio.v9i1.13954.
R. Ambarwati, Aidinil Zetra, and Syahrizal, “Efektivitas Sosialisasi Pemilu 2019 KPU Kabupaten Indragiri Hulu,” J. Niara, vol. 15, no. 3, pp. 571–580, 2023, doi: 10.31849/niara.v15i3.9280.
M. Renaldi, U. Juhardi, A. Munandar, A. Karolina, and W. Seprianti, “Manajemen Pengarsipan Jaringan Dokumentasi Dan Informasi Hukum (Jdih) Kpu Provisi Bengkulu,” J. Ilm. Mhs. Kuliah Kerja Nyata, vol. 2, no. 2, pp. 224–230, 2022, doi: 10.36085/jimakukerta.v2i2.3390.
H. Syah and A. Witanti, “Analisis Sentimen Masyarakat Terhadap Vaksinasi Covid-19 Pada Media Sosial Twitter Menggunakan Algoritma Support Vector Machine (Svm),” J. Sist. Inf. dan Inform., vol. 5, no. 1, pp. 59–67, 2022, doi: 10.47080/simika.v5i1.1411.
P. Arsi, R. Wahyudi, and R. Waluyo, “Optimasi SVM Berbasis PSO pada Analisis Sentimen Wacana Pindah Ibu Kota Indonesia,” J. RESTI (Rekayasa Sist. dan Teknol. Informasi), vol. 5, no. 2, pp. 231–237, 2021, doi: 10.29207/resti.v5i2.2698.
Alfandi Safira and F. N. Hasan, “Analisis Sentimen Masyarakat Terhadap Paylater Menggunakan Metode Naive Bayes Classifier,” Zo. J. Sist. Inf., vol. 5, no. 1, pp. 59–70, 2023, doi: 10.31849/zn.v5i1.12856.
F. N. Hasan and M. Dwijayanti, “Analisis Sentimen Ulasan Pelanggan Terhadap Layanan Grab Indonesia Menggunakan Multinominal Naïve Bayes Classifier,” J. Linguist. Komputasional, vol. 4, no. 2, pp. 52–58, 2021, doi: https://doi.org/10.26418/jlk.v4i2.61.
W. Khofifah, D. N. Rahayu, and A. M. Yusuf, “Analisis Sentimen Menggunakan Naive Bayes Untuk Melihat Review Masyarakat Terhadap Tempat Wisata Pantai Di Kabupaten Karawang Pada Ulasan Google Maps,” J. Interkom J. Publ. Ilm. Bid. Teknol. Inf. dan Komun., vol. 16, no. 4, pp. 171–180, 2022, doi: 10.35969/interkom.v16i4.192.
F. Sidik, I. Suhada, A. H. Anwar, and F. N. Hasan, “Analisis Sentimen Terhadap Pembelajaran Daring Dengan Algoritma Naive Bayes Classifier,” J. Linguist. Komputasional, vol. 5, no. 1, pp. 34–43, 2022, doi: 10.26418/jlk.v5i1.79.
E. Fitriani, “Perbandingan Algoritma C4.5 Dan Naïve Bayes Untuk Menentukan Kelayakan Penerima Bantuan Program Keluarga Harapan,” Sistemasi, vol. 9, no. 1, pp. 103–116, 2020, doi: 10.32520/stmsi.v9i1.596.
T. Astuti and Y. Astuti, “Analisis Sentimen Review Produk Skincare Dengan Naïve Bayes Classifier Berbasis Particle Swarm Optimization (PSO),” J. Media Inform. Budidarma, vol. 6, no. 4, pp. 1806–1815, 2022, doi: 10.30865/mib.v6i4.4119.
N. Luh et al., “ANALISIS SENTIMEN ULASAN VILLA DI UBUD MENGGUNAKAN METODE NAÏVE BAYES , DECISION TREE , DAN K-NN Jurnal Nasional Pendidikan Teknik Informatika?: JANAPATI | 206,” vol. 11, no. 3, pp. 205–216, 2022, doi: https://doi.org/10.23887/janapati.v11i3.49450.
N. Q. Rizkina and F. N. Hasan, “Analisis Sentimen Komentar Netizen Terhadap Pembubaran Konser NCT 127 Menggunakan Metode Naive Bayes,” vol. 4, no. 4, pp. 1136–1144, 2023, doi: 10.47065/josh.v4i4.3803.
I. T. Julianto, “Analisis Sentimen Terhadap Sistem Informasi Akademik Institut Teknologi Garut,” J. Algoritm., vol. 19, no. 1, pp. 458–465, 2022, doi: 10.33364/algoritma/v.19-1.1112.
D. Hermawan, M. Akhsanal, Z. Wahyudi, A. Ariyanto, and D. Dwi, “05. Optimasi Analisis Sentimen Pada Twitter Olshop,” vol. 6, no. September, pp. 821–828, 2022, doi: http://dx.doi.org/10.30645/j-sakti.v6i2.493.
I. R. Afandi, I. F. Hanif, F. N. Hasan, E. Sinduningrum, Z. Halim, and N. Pratiwi, “Analisis Sentimen Opini Masyarakat Terkait Penyelenggaraan Sistem Elektronik Menggunakan Metode Logistic Regression,” J. Linguist. Komputasional, vol. 5, no. 2, pp. 77–84, 2022, doi: https://doi.org/10.26418/jlk.v5i2.103.
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