Klasifikasi Sentimen Masyarakat di Media Sosial Twitter terhadap Calon Presiden 2024 Prabowo Subianto dengan Metode K-NN
DOI:
https://doi.org/10.30865/klik.v3i6.890Keywords:
Sentiment Classification; K-NN; Twitter; Presidential Candidates; Prabowo SubiantoAbstract
The 2024 Republic of Indonesia Presidential Election is a democratic stage to determine the President of the Republic of Indonesia and Vice President of the State of Indonesia for the 2024-2029 period which is scheduled to take place on Wednesday, 14 February 2024. This election is the fifth direct presidential and vice presidential election in Indonesia. Several parties have currently nominated or selected their presidential candidates for the 2024 presidential election. Three presidential candidates have emerged, namely Prabowo Subianto, Ganjar Pranowo, and Anies Baswedan. Based on a survey, Prabowo Subianto is the presidential candidate (capres) with the highest electability compared to other competitors. The society's view of the 2024 presidential candidate, especially Prabowo Subianto, has raised many pros and cons. Society's view can be seen on social media, like one of this is the Twitter. This study aims to classify public sentiment towards the Presidential Candidate (capres) Prabowo Subianto on Twitter. The amount of data used is 2100 tweets which are collected based on the keywords "Presidential Candidate" and "Prabowo Subianto". The application of the K-Nearest Neighbor (K-NN) method with weighting in the form of TF-IDF and Feature Selection in the form of Threshold will be implemented using Google Colab. Based on the results of testing the K-NN method using the confusion matrix at seven K values, namely (3,5,7,9,11,13,15) with the comparisons used 70:30, 80:20, 90:10 the highest accuracy was obtained at K = 5 at the ratio of training data and test data 80:20.
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W. A. Wibawana, “Sejarah Pemilu di Indonesia dari Awal Sampai Sekarang,” detiknews, 2023. https://news.detik.com/pemilu/d-6526532/sejarah-pemilu-di-indonesia-dari-awal-sampai-sekarang#:~:text=Pilpres 2024 adalah pemilihan umum yang akan menjadi,secara serentak pada tanggal 14 Februari 2024 mendatang. (accessed Jun. 09, 2023).
F. C. Farisa, “Sejarah Dimulainya Pemilu Presiden dan Wakil Presiden Secara Langsung,” KOMPAS.com, 2022. https://nasional.kompas.com/read/2022/05/31/12112831/sejarah-dimulainya-pemilu-presiden-dan-wakil-presiden-secara-langsung (accessed Jun. 09, 2023).
F. C. Farisa, “Pilpres 2024 Diprediksi Diikuti 3 Capres: Ganjar, Prabowo, dan Anies,” KOMPAS.com, 2023.
F. C. Farisa, “Survei Indikator: Elektabilitas Prabowo Bersaing Ketat dengan Ganjar, Anies Urutan Ketiga,” KOMPAS.com, 2023.
M. Aulidya, “Manfaat, Fitur, dan Fungsi Twitter: Mengenal Lebih Dekat Media Sosial yang Populer Saat ini,” kompasiana, 2023. https://www.kompasiana.com/mishelaulidya7261/643bb5c9a7e0fa33b71c51e3/manfaat-fitur-dan-fungsi-twitter-mengenal-lebih-dekat-media-sosial-yang-populer-saat-ini (accessed Jun. 09, 2023).
R. T. Prasetio, “Seleksi Fitur dan Optimasi Parameter K-NN Berbasis Algoritma Genetika pada Dataset Medis,” J. Responsif Ris. Sains dan Inform., vol. 2, no. 2, pp. 213–221, 2020, doi: 10.51977/jti.v2i2.319.
F. Rizqi Irawan, “Analisis Sentimen Terhadap Pengguna Gojek Menggunakan Metode K-Nearset Neighbors,” JIKO (Jurnal Inform. dan Komputer), vol. 5, no. 1, pp. 62–68, 2022, doi: 10.33387/jiko.v5i1.4267.
A. D. Adhi Putra, “Analisis Sentimen pada Ulasan pengguna Aplikasi Bibit Dan Bareksa dengan Algoritma KNN,” JATISI (Jurnal Tek. Inform. dan Sist. Informasi), vol. 8, no. 2, pp. 636–646, 2021, doi: 10.35957/jatisi.v8i2.962.
K. A. Nugraha, “Pembentukan Dataset Token Sentimen Berdasarkan Akun Instagram,” J. Buana Inform. Vol., vol. 12, no. April, pp. 68–77, 2021.
E. H. Muktafin and P. Kusrini, “Sentiments analysis of customer satisfaction in public services using K-nearest neighbors algorithm and natural language processing approach,” Telkomnika (Telecommunication Comput. Electron. Control., vol. 19, no. 1, pp. 146–154, 2021, doi: 10.12928/TELKOMNIKA.V19I1.17417.
R. Damarta, A. Hidayat, and A. S. Abdullah, “The application of k-nearest neighbors classifier for sentiment analysis of PT PLN (Persero) twitter account service quality,” J. Phys. Conf. Ser., vol. 1722, no. 1, 2021, doi: 10.1088/1742-6596/1722/1/012002.
N. G. Yudiarta, M. Sudarma, and W. G. Ariastina, “Pengelompokan Berita Pada Unstructured Textual Data,” vol. 17, no. 3, pp. 339–344, 2018.
F. Rozi, F. Sukmana, and M. N. Adani, “Pengelompokkan Judul Buku dengan Menggunakan Algoritma K-Nearest Neighbor ( K-NN ) dan Term Frequency – Inverse Document Frequency ( TF-IDF ),” vol. 6, no. 3, pp. 1–5, 2022.
V. Bolón-canedo and A. Alonso-betanzos, “Ensembles for feature selection?: A review and future trends,” ELSEVIER, vol. 52, no. May 2018, pp. 1–12, 2019, doi: 10.1016/j.inffus.2018.11.008.
R. M. Candra and A. Nanda Rozana, “Klasifikasi Komentar Bullying pada Instagram Menggunakan Metode K-Nearest Neighbor,” IT J. Res. Dev., vol. 5, no. 1, pp. 45–52, 2020, doi: 10.25299/itjrd.2020.vol5(1).4962.
A. Yoga Pratama, Y. Umaidah, and Voutama, “Analisis Sentimen Media Sosial Twitter dengan Algoritma K-Nearest Neighbor dan Seleksi Fitur Chi-Square (Kasus Omnibus Law Cipta Kerja),” J. Sains Komput. Inform. (J-SAKTI, vol. 5, no. 2, pp. 897–910, 2021.
T. D. Arista, M. Fikry, and L. Oktavia, “Klasifikasi Sentimen Masyarakat di Twitter terhadap Kenaikan Harga BBM dengan Metode K-NN,” JUKI, vol. 5, pp. 140–150, 2023.
A. F. Rahman, “Klasifikasi Tweet di Twitter dengan Menggunakan Metode K-Nearest Neighbor,” J. Sist. Inf. dan Teknol., vol. 4, pp. 64–69, 2022, doi: 10.37034/jsisfotek.v4i2.125.
M. T. Diwandanu, “Analisis Sentimen terhadap Twit Maxim pada Twitter Menggunakan R Programming dan K-Nearest Neighbors,” J. Ilm. Inform. Komput., vol. 28, pp. 1–16, 2023.
R. Kosasih and A. Alberto, “Analisis Sentimen Produk Permainan Menggunakan Metode TF-IDF Dan Algoritma K-Nearest Neighbor,” InfoTekJar J. Nas. Inform. dan Teknol. Jar., vol. 6, no. 1, pp. 134–139, 2021.
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