Analisis Sentimen Masyarakat Terhadap Kenaikan Biaya Haji Tahun 2023 Menggunakan Metode Naïve Bayes Classifier
DOI:
https://doi.org/10.30865/klik.v4i3.1457Keywords:
Increase In Hajj Costs In 2023; Twitter; Classification; Sentiment Analysis; Naïve Bayes ClassifiefAbstract
The Indonesian government through a meeting of the Ministry of Religion and Commission IVIII of the DPR-RI agreed on the cost of organizing the Hajj pilgrimage (BPIH) i1444 iH/2023 iM, an average of IDR 90,050,637.26 per irregular pilgrimage. However, this policy gave rise to various public responses. The public's anger regarding the increase in Hajj fees in 2023 was found on the social media iTwitter. In this study, we conducted a sentiment classification analysis of Tweets to determine public opinion regarding the increase in Hajj costs in 2023 using the naïve Bayes classifier method because this method tends to be simple and easy to use. The data set used was 3000 tweets with a total of 1866 positive data, 415 negative data. This research resulted in an accuracy value of 81.46% in the 70:30 data division, in the 80:20 data division, namely 80.74% and in the data division. 90:10 which is 79.04. In this research, there were more positive responses from the public, this proves that the increase in Hajj costs in 2023 can be accepted by the public. The highest accuracy in this study was 81.46% with a 70:30 data split. It is recommended that further research use other algorithms to see a comparison of the results of different algorithms in classifying public sentiment regarding the increase in the cost of Hajj in 2023.
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A. J. Showail, “Solving Hajj and Umrah Challenges Using Information and Communication Technology: A Survey,” IEEE Access, vol. 10, no. May, pp. 75404–75427, 2022, doi: 10.1109/ACCESS.2022.3190853.
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, p. 34, 2022, doi: 10.26418/jlk.v5i1.79.
M. F. Muzakki, J. Jondri, and U. R. Febrian, “Analisis Sentimen Mahasiswa Terhadap Fasilitas Universitas Telkom Menggunakan Metode Jaringan Saraf Tiruan Dan Tf-Idf,” e-Prodeceeding Eng., vol. 6, no. 2, pp. 8608–8616, 2019.
O. I. Gifari, M. Adha, F. Freddy, and F. F. S. Durrand, “Analisis Sentimen Review Film Menggunakan TF-IDF dan Support Vector Machine,” J. Inf. Technol., vol. 2, no. 1, pp. 36–40, 2022, doi: 10.46229/jifotech.v2i1.330.
S. J. S. Tyas, M. Febianah, F. Solikhah, A. L. Kamil, and W. A. Arifin, “Analisis Perbandingan Algoritma Naive Bayes Dan C.45 Dalam Klasifikasi Data Mining Untuk Memprediksi Kelulusan,” J. Teknol. Inf. Dan Komun., vol. 8, no. 1, pp. 86–99, 2021, [Online]. Available: https://jurnal.plb.ac.id/index.php/tematik/article/view/576/365
B. Gunawan, H. S. Pratiwi, and E. E. Pratama, “Sistem Analisis Sentimen pada Ulasan Produk Menggunakan Metode Naive Bayes,” J. Edukasi dan Penelit. Inform., vol. 4, no. 2, p. 113, 2018, doi: 10.26418/jp.v4i2.27526.
Aldinata, A. M. Soesanto, V. C. Chandra, and D. Suhartono, “Sentiments comparison on Twitter about LGBT,” Procedia Comput. Sci., vol. 216, pp. 765–773, 2023, doi: 10.1016/j.procs.2022.12.194.
M. Wongkar and A. Angdresey, “Sentiment Analysis Using Naive Bayes Algorithm Of The Data Crawler: Twitter,” Proc. 2019 4th Int. Conf. Informatics Comput. ICIC 2019, pp. 1–5, 2019, doi: 10.1109/ICIC47613.2019.8985884.
F. E. Purwiantono and A. Aditya, “Klasifikasi Sentimen Sara, Hoaks Dan Radikal Pada Postingan Media Sosial Menggunakan Algoritma Naive Bayes Multinomial Text,” J. Tekno Kompak, vol. 14, no. 2, p. 68, 2020, doi: 10.33365/jtk.v14i2.709.
I. Verawati and B. S. Audit, “Algoritma Naïve Bayes Classifier Untuk Analisis Sentiment Pengguna Twitter Terhadap Provider By.u,” J. Media Inform. Budidarma, vol. 6, no. 3, p. 1411, 2022, doi: 10.30865/mib.v6i3.4132.
M. Hudha, E. Supriyati, and T. Listyorini, “Analisis Sentimen Pengguna Youtube Terhadap Tayangan #Matanajwamenantiterawan Dengan Metode Naïve Bayes Classifier,” JIKO (Jurnal Inform. dan Komputer), vol. 5, no. 1, pp. 1–6, 2022, doi: 10.33387/jiko.v5i1.3376.
R. T. Aldisa and P. Maulana, “Analisis Sentimen Opini Masyarakat Terhadap Vaksinasi Booster COVID- 19 Dengan Perbandingan Metode Naive Bayes , Decision Tree dan SVM,” Build. Informatics, Technol. Sci., vol. 4, no. 1, pp. 106–109, 2022, doi: 10.47065/bits.v4i1.1581.
F. Wulandari, E. Haerani, M. Fikry, and E. Budianita, “Analisis sentimen larangan penggunaan obat sirup menggunakan algoritma naive bayes classifier,” vol. 4, no. 1, pp. 88–96, 2023.
A. Aziz, “Analisis Sentimen Identifikasi Opini Terhadap Produk, Layanan dan Kebijakan Perusahaan Menggunakan Algoritma TF-IDF dan SentiStrength,” J. Sains Komput. Inform. (J-SAKTI, vol. 6, no. 1, p. 115, 2022.
J. A. Septian, T. M. Fachrudin, and A. Nugroho, “Analisis Sentimen Pengguna Twitter Terhadap Polemik Persepakbolaan Indonesia Menggunakan Pembobotan TF-IDF dan K-Nearest Neighbor,” J. Intell. Syst. Comput., vol. 1, no. 1, pp. 43–49, 2019, doi: 10.52985/insyst.v1i1.36.
T. Sanubari, C. Prianto, and N. Riza, Odol (One Desa One Product Unggulan Online) Penerapan Metode Naïve Bayes Pada pengembangan Aplikasi E-Comerce Menggunakan Codeigniter. Bandung: Kreatif Industri Nusantara, 2020.
I. W. Saputro and B. W. Sari, “Uji Performa Algoritma Naïve Bayes untuk Prediksi Masa Studi Mahasiswa,” Creat. Inf. Technol. J., vol. 6, no. 1, p. 1, 2020, doi: 10.24076/citec.2019v6i1.178.
D. A. Pratiwi, R. M. Awangga, and M. Y. H. Setyawan, Seleksi Calon Kelulusan Tepat Waktu Mahasiswa Teknik Informaika Menggunakan Metode Naive Bayes, Pertama. Bandung: Kreatif Industri Nusantara, 2020.
D. Normawati and S. A. Prayogi, “Implementasi Naïve Bayes Classifier Dan Confusion Matrix Pada Analisis Sentimen Berbasis Teks Pada Twitter,” J. Sains Komput. Inform. (J-SAKTI, vol. 5, no. 2, pp. 697–711, 2021, [Online]. Available: https://ejurnal.tunasbangsa.ac.id/index.php/jsakti/article/view/369/348
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