Sentiment Analysis of Unemployment in Indonesia During and Post COVID-19 on X (Twitter) Using Naïve Bayes and Support Vector Machine

  • Putu Ayulia Setiawati Udayana University, Indonesia
  • I Made Agus Dwi Suarjaya Udayana University, Indonesia
  • I Nyoman Prayana Trisna Udayana University, Indonesia
DOI: 10.51519/journalisi.v6i2.713
Keywords: Unemployment, tweet, TF-IDF, Naïve Bayes, Support Vector Machine

Abstract

The COVID-19 pandemic has impacted health, economy, and society. Social distancing measures and quarantine policies have restricted economic activities, leading to downturns in COVID-19-affected regions and a subsequent rise in unemployment rates, particularly in urban areas. Concurrently, there has been a remarkable surge in the utilization of the X (Twitter) platform, with Indonesia ranking 6th globally in X (Twitter) users. This study aims to understand the diverse perspectives of society on unemployment and the factors influencing society's views on unemployment through sentiment analysis of X (Twitter) data. By analyzing 576,764 tweets from April 2020 to October 2023, tweets are categorized into positive, neutral, and negative classes. Classification model was built to classify tweet data by implementing TF-IDF for word weighting, and a pair of machine learning algorithms, Naïve Bayes and Support Vector Machine (SVM). Model evaluation yielded the highest accuracy of 81.5% using Naïve Bayes. The classification outcomes highlight prevalent negative perceptions of unemployment among Indonesians, totaling 50.03%. This research contributes to the literature by providing a large-scale analysis of social media data to uncover public sentiment trends and offering insights for policymakers to address unemployment and improve welfare.

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References

S. Panneer et al., “Health, Economic and Social Development Challenges of the COVID-19 Pandemic: Strategies for Multiple and Interconnected Issues,” Healthcare (Switzerland), vol. 10, no. 5, May 2022, doi: 10.3390/healthcare10050770.

N. Aeni, “Pandemi COVID-19: Dampak Kesehatan, Ekonomi, dan Sosial COVID-19 Pandemic: The Health, Economic, and Social Effects,” vol. 17, no. Juni, pp. 17–34, 2021, doi: https://doi.org/10.33658/jl.v17i1.249.

F. Rizal and H. Mukaromah, “Kebijakan Pemerintah Indonesia Dalam Mengatasi Masalah Pengangguran Akibat Pandemi Covid 19,” 2021.

N. Rihhadatul’aisyi, S. Muthmainnah, T. W. Putri, H. P. Zahra, and F. T. Febrian, “Efek Twitter di Masa Pandemi COVID-19 pada Sikap dan Perilaku,” Jurnal Ilmu Komunikasi, vol. 19, no. 2, p. 205, Oct. 2021, doi: 10.31315/jik.v19i2.4178.

R. Satria, I. M. A. D. Suarjaya, and I. P. A. E. Pratama, “Sentiment Analisi Antusias Masyarakat Terhadap Sampah Plastik Dengan Menggunakan Metode Support Vector Machine (SVM),” JITTER- Jurnal Ilmiah Teknologi dan Komputer, vol. 3, no. 1, 2022.

E. S. Romaito, M. K. Anam, R. Rahmaddeni, and A. N. Ulfah, “Perbandingan Algoritma Svm Dan Nbc Dalam Analisa Sentimen Pilkada Pada Twitter,” CSRID (Computer Science Research and Its Development Journal), vol. 13, no. 3, p. 169, Nov. 2021, doi: 10.22303/csrid.13.3.2021.169-179.

K. M. A. Candrayani, I. M. A. D. Suarjaya, and A. A. K. A. C. Wiranatha, “Analisis Sentimen Pembelajaran Daring Era Pandemi COVID-19 Menggunakan Naive Bayes Dan SVM,” TEMATIK, vol. 10, no. 1, pp. 47–53, Jun. 2023, doi: 10.38204/tematik.v10i1.1274.

M. Rizal Ramli and H. Sulastri, “Sentiment Analysis Of Student Opinion Related To Online Learning Using Naïve Bayes Classifier Algorithm And SVM With Adaboost On Twitter Social Media,” Jurnal Informatika dan Teknologi Informasi, vol. 20, no. 2, pp. 187–201, 2023, doi: 10.31515/telematika.v20i2.8827.

M. Meenakshi and J. Kaur, “Analysis of Employment-Related Sentiment in Social Media in India,” Mathematical Statistician and Engineering Applications, vol. 71, no. 4, pp. 10277–10288, 2022.

B. W. Kurniadi, N. H. Matondang, and D. S. Prasvita, “Penerapan Algoritma Naive Bayes Untuk Analisis Sentimen Penggunaan Aplikasi Jobstreet Implementation of Naive Bayes Algorithm For Sentiment Analysis Of The Use Of Jobstreet Application,” Agustus, vol. 21, no. 3, pp. 523–533, 2022, doi: https://doi.org/10.33633/tc.v21i3.6361.

P. H. Prastyo, I. Ardiyanto, and R. Hidayat, “Indonesian Sentiment Analysis: An Experimental Study of Four Kernel Functions on SVM Algorithm with TF-IDF,” in 2020 International Conference on Data Analytics for Business and Industry: Way Towards a Sustainable Economy, ICDABI 2020, Institute of Electrical and Electronics Engineers Inc., Oct. 2020. doi: 10.1109/ICDABI51230.2020.9325685.

P. S. M. Suryani, L. Linawati, and K. O. Saputra, “Penggunaan Metode Naïve Bayes Classifier pada Analisis Sentimen Facebook Berbahasa Indonesia,” Majalah Ilmiah Teknologi Elektro, vol. 18, no. 1, p. 145, May 2019, doi: 10.24843/mite.2019.v18i01.p22.

S. Khomsah, “Naive Bayes Classifier Optimization on Sentiment Analysis of Hotel Reviews,” Jurnal Penelitian Pos dan Informatika, vol. 10, no. 2, pp. 157–168, Dec. 2020, doi: 10.17933/jppi.2020.100206.

M. A. S. addam and E. D. Kurniawan, “Analisis Sentimen Fenomena PHK Massal Menggunakan Naive Bayes dan Support Vector Machine,” Jurnal Informatika: Jurnal pengembangan IT (JPIT), vol. 8, no. 3, pp. 226–233, 2023, doi: https://doi.org/10.30591/jpit.v8i3.4884.

E. Cengil and A. Çınar, “The effect of deep feature concatenation in the classification problem: An approach on COVID-19 disease detection,” Int J Imaging Syst Technol, vol. 32, no. 1, pp. 26–40, Sep. 2021, doi: 10.1002/ima.22659.

S. N. J. Fitriyyah, N. Safriadi, and E. E. Pratama, “Analisis Sentimen Calon Presiden Indonesia 2019 dari Media Sosial Twitter Menggunakan Metode Naive Bayes,” JEPIN (Jurnal Edukasi dan Penelitian Informatika) , vol. 5, no. 3, pp. 279–285, 2019, doi: http://dx.doi.org/10.26418/jp.v5i3.34368.

T. A. Azzahra et al., “Perbandingan Efektivitas Naïve Bayes dan SVM dalam Menganalisis Sentimen Kebencanaan di Youtube,” Jurnal Media Informatika Budidarma, vol. 8, no. 1, pp. 312–322, 2024, doi: 10.30865/mib.v8i1.7186.

S. I. Nurhafida and F. Sembiring, “Analisis Sentimen Aplikasi Novel Online Di Google Play Store Menggunakan Algoritma Support Vector Machine (SVM),” Jurnal Sains Komputer & Informatika (J-SAKTI), vol. 6, no. 1, pp. 317–327, 2022.

Published
2024-06-13
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How to Cite
Setiawati, P., Suarjaya, I. M., & Trisna, I. N. (2024). Sentiment Analysis of Unemployment in Indonesia During and Post COVID-19 on X (Twitter) Using Naïve Bayes and Support Vector Machine. Journal of Information Systems and Informatics, 6(2), 662-675. https://doi.org/10.51519/journalisi.v6i2.713
Issue
Vol 6 No 2 (2024): Journal of Information Systems and Informatics
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