Sentiment Analysis of Rice Price Increase on Facebook Using Naïve Bayes Algorithm

  • Rijal Universitas Darwan Ali
  • Eka Prasetyaningrum Universitas Darwan Ali
  • Agung Purwanto Universitas Darwan Ali
  • Abdul Aziz Universitas Darwan Ali
Keywords: rice, sentiment, Facebook, Naive Bayes

Abstract

This study explores public sentiment towards the rice price increase in Indonesia using data from social media posts on Facebook. As a crucial staple commodity, rice prices significantly impact the economy and social life of the community. In this study, data was collected from Facebook using Instant Data Scraper during the period from January to May. The collected data underwent a cleaning process, and 200 data points were manually labeled as training data. The text preprocessing steps included tokenization, case folding, and stopword removal. Subsequently, TF-IDF weighting was applied to determine the importance of each word in the documents. The processed data was then analyzed using the Naive Bayes algorithm to classify positive and negative sentiments. The analysis results showed that out of 428 test data points, the Naive Bayes algorithm successfully identified 237 reviews as positive sentiment and 191 reviews as negative sentiment. Based on the obtained data, this study is expected to provide insights for the government and policymakers in managing rice price policies and improving public communication strategies, as well as anticipating the social impact of rice price increases.

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DAFTAR PUSTAKA
[1] D. H. Darwanto and E. S. Rahayu, “Analisis Faktor-Faktor Yang Mempengaruhi Impor Beras Indonesia,” Caraka Tani J. Sustain. Agric., vol. 23, no. 1, p. 1, 2017, doi: 10.20961/carakatani.v23i1.13732.
[2] N. Lidwina, A. Retno, and I. H. Nisa, “Analisis Kenaikan Harga Beras Terhadap Mahasiswa Universitas Negeri Semarang,” KIRANA Soc. Sci. J., vol. 1, no. 1, pp. 8–15, 2024, [Online]. Available: https://ejournal.sagita.or.id/index.php/kirana
[3] B. Irawan, “Fenomena Anomali Iklim El Nino dan La Nina: Kecenderungan Jangka Panjang dan Pengaruhnya terhadap Produksi Pangan,” Forum Penelit. Agro Ekon., vol. 24, no. 1, p. 28, 2016, doi: 10.21082/fae.v24n1.2006.28-45.
[4] E. Usman and M. Rahma, “Analysis of Factors for Increasing Rice Prices in Kolaka Regency,” vol. 3, no. 1, pp. 1–12, 2024.
[5] F. Apri Wenando, R. Hayami, S. Soni, A. Fitria, and D. Shifana, “Sentimen Analisis Masyarakt terhadap Kasus Penembakan Brigadir J Menggunakan Algoritma Naïve Bayes Classifier,” J. CoSciTech (Computer Sci. Inf. Technol., vol. 4, no. 2, pp. 484–490, 2023, doi: 10.37859/coscitech.v4i2.5686.
[6] Syahril Dwi Prasetyo, Shofa Shofiah Hilabi, and Fitri Nurapriani, “Analisis Sentimen Relokasi Ibukota Nusantara Menggunakan Algoritma Naïve Bayes dan KNN,” J. KomtekInfo, vol. 10, pp. 1–7, 2023, doi: 10.35134/komtekinfo.v10i1.330.
[7] N. Nofiyani and W. Wulandari, “Implementasi Electronic Data Processing Untuk meningkatkan Efektifitas dan Efisiensi Pada Text Mining,” J. Media Inform. Budidarma, vol. 6, no. 3, p. 1621, 2022, doi: 10.30865/mib.v6i3.4332.
[8] S. Khairunnisa, A. Adiwijaya, and S. Al Faraby, “Pengaruh Text Preprocessing terhadap Analisis Sentimen Komentar Masyarakat pada Media Sosial Twitter (Studi Kasus Pandemi COVID-19),” J. Media Inform. Budidarma, vol. 5, no. 2, p. 406, 2021, doi: 10.30865/mib.v5i2.2835.
[9] I. T. Julianto, “Analisis Sentimen Terhadap Sistem Informasi Akademik Institut Teknologi Garut,” J. Algoritm., vol. 19, no. 1, pp. 449–456, 2022, doi: 10.33364/algoritma/v.19-1.1112.
[10] D. Angraina and A. Putri, “Analisis Sentimen Pengguna Aplikasi Google Meet Menggunakan Algoritma Support Vector Machine,” J. CoSciTech (Computer Sci. Inf. Technol., vol. 3, no. 3, pp. 472–478, 2022, doi: 10.37859/coscitech.v3i3.4260.
[11] T. Sanubari, C. Prianto, and N. Riza, Odol (one desa one product unggulan online) penerapan metode Naive Bayes pada pengembangan aplikasi e-commerce menggunakan Codeigniter. 2020.
Published
2024-08-19
How to Cite
Rijal, Eka Prasetyaningrum, Agung Purwanto, & Abdul Aziz. (2024). Sentiment Analysis of Rice Price Increase on Facebook Using Naïve Bayes Algorithm. Jurnal CoSciTech (Computer Science and Information Technology), 5(2), 381-390. https://doi.org/10.37859/coscitech.v5i2.7473
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