Study of Public Sentiment Towards Beauty Products Using A Machine Learning Approach: Random Forest Analysis On Social Media

Authors

  • Tresya Noviania Pasaribu Prima Indonesia University, Indonesia
  • Juliansyah Putra Tanjung Prima Indonesia University, Indonesia
  • Dosma Hutauruk Prima Indonesia University, Indonesia
  • Endang Sapriana Hutagalung Prima Indonesia University, Indonesia
  • Saputra Silitonga Prima Indonesia University, Indonesia

DOI:

10.33395/sinkron.v8i3.13969

Keywords:

Sentiment Analysis; Social Media Data; Beauty Products; Machine Learning; Random Forest

Abstract

In this digitalized era, the development of technology and the internet has brought significant changes in various aspects of life, including the way we shop. The trend of online shopping is increasingly prevalent and favored by the public, not least for cosmetic products. This research uses a quantitative approach to analyze public opinion or sentiment towards beauty products, especially beauty products. The data used in this research comes from online platforms. This research uses a beauty product dataset obtained from Kaggle. This research uses the Random Forest algorithm to analyze the data and produce findings, This algorithm is one of the advanced tools in Machine Learning that is focused on sorting data into the right categories, which in this context is used to classify public sentiment towards beauty products into categories such as positive, negative or neutral. Random Forest achieved a very high accuracy rate of 94.68% in the evaluation. However, it should be noted that the positive class has a low recall (25%) and a low F1-score (40%), indicating that the model may struggle to detect positive sentiment towards beauty products beauty products. In general, the model did well in classifying neutral and negative sentiments. Sentiment analysis shows that the majority of public sentiment towards beauty products is neutral, with a significant amount of negative and positive sentiment. It is evident that user opinions are informative or descriptive without conveying strong positive or negative emotions.

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How to Cite

Tresya Noviania Pasaribu, Tanjung, J. P., Dosma Hutauruk, Endang Sapriana Hutagalung, & Saputra Silitonga. (2024). Study of Public Sentiment Towards Beauty Products Using A Machine Learning Approach: Random Forest Analysis On Social Media. Sinkron : Jurnal Dan Penelitian Teknik Informatika, 8(3), 2088-2098. https://doi.org/10.33395/sinkron.v8i3.13969

Issue

Vol. 8 No. 3 (2024): Research Artikel Volume 8 Issue 3, July 2024

Section

Articles

License

Copyright (c) 2024 Juliansyah Putra Tanjung, Tresya Noviania Pasaribu, Dosma Hutauruk, Endang Sapriana Hutagalung, Saputra Silitonga

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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