PUBLIC SENTIMENT ANALYSIS THROUGH TWITTER ON SALES TAX ON LUXURY GOOD INCENTIVES USING MACHINE LEARNING METHOD

Igra; Amy Fontanella; Hendrick

doi:10.51200/mjbe.v9i2.3928

Authors

Igra Politeknik Negeri Padang
Amy Fontanella Politeknik Negeri Padang
Hendrick Politeknik Negeri Padang

DOI:

https://doi.org/10.51200/mjbe.v9i2.3928

Keywords:

sales tax in luxury goods, twitter, machine learning, sentiment analysis, Natural Language Toolkit (NLTK)

Abstract

The government’s policy on Incentives on Sales Tax on Luxury Goods on the Delivery of Taxable Goods Classified as Luxury in the Form of Certain Motorized Vehicles Covered by the Government for the 2021 fiscal year during the pandemic has invited pros and cons among the public, including twitter users. This study aims to identify and analyze public sentiment toward the government’s policy. The method used is machine learning, namely the Natural Language Toolkit (NLTK) analysis. The Results of this study obtained 49 positive sentiments and 65 negative sentiments that describe support, opposition and critical discourse on the policy with a data accuracy rate of 94.23%. The government needs to consider public sentiment and can be taken into consideration in determining the impact of a policy on the economy from all walks of life.

References

Safrina, N., Soeharto, A., & Asrina, A. S. (2019). “Menjaga Marwah” insentif perpajakan yang berdampak pada penerimaan pajak di Indonesia tahun 2019. Jurnal Riset Terapan Akuntansi, 4(1), 2020

Pabreja, Kavita (2017). Sentiment analysis using twitter data. International Journal of-Applied Research, 3(7), 660-662.

Haryani, C. A., Tohari, H., & Nurrahman, Y. A. (2019). Sentimen Analisis Kepuasan Pelanggan E-commerce menggunakan Lexicon Classification dengan R. Konferensi Nasional Sistem Informasi 2018.

Alizah, M. D., Nugrogo, A., Radiyah., U., & Gata, Windu. (2020). Sentimen Analisis Terkait Lockdown pada Social Media Twitter. Indonesian Journal on Software Engineering.

Rumata, V. M., (2017). Analisis Isi Kualitatif Twitter “#TaxAmnesty” dan “#AmnestyPajak”: An approach for sentiment analysis of GTS Tweets Using Words Popularity Versus Polarity Generation Sourav Das1, Dipankar Das2, and Anup Kumar Kolya3

Shayaa, S., Jaafar, N. I., Bahri, S., Sulaiman, A., Seuk Wai, P., Wai Chung, Y., & …Al-Garadi, M.

A. (2018). Sentiment analysis of big data: Methods, applications, and open challenges.IEEE Access, 6, 37807–37827. https://doi.org/10.1109/ACCESS.2018.2851311

Anchal Kathuria Avinash Sharma. (2020). A comparative study of various approaches for sentiment analysis of twitter data.