Analsis Sentimen Churn Pelanggan dalam Layanan Streaming NETFLIX di X Menggunakan Metode IndoBERT

Authors

  • Farencia Levis Universitas Pelita Harapan
  • Cindy Chuwardi Universitas Pelita Harapan
  • Yoshe Wuvanka Universitas Pelita Harapan
  • Eveleen Huandra Universitas Pelita Harapan

DOI:

https://doi.org/10.54259/jdmis.v3i2.4281

Keywords:

Sentimen, Churn, IndoBERT, NETFLIX, Media Sosial, Text Mining

Abstract

This study aims to analyze customer sentiment toward Netflix’s streaming service as expressed on social media platform X (formerly Twitter), in order to identify potential churn. The research employs a combination of Text Mining and Sentiment Analysis methods, utilizing the IndoBERT-based Natural Language Processing (NLP) model. Data was collected using web scraping techniques with keywords indicating complaints or cancellation of Netflix subscriptions. The text data underwent preprocessing steps including case folding, cleaning, lemmatization, and tokenization. Sentiment classification results showed that most tweets expressed negative sentiment, suggesting a high risk of customer churn. Key factors driving negative sentiment include subscription pricing, login policy restrictions, and the cancellation of popular content. These findings can assist Netflix’s marketing and product development teams in creating data-driven retention strategies. Furthermore, the study demonstrates that the IndoBERT model is effective in classifying Indonesian-language social media opinions into positive, neutral, and negative sentiment categories.

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Published

2025-08-31

How to Cite

Levis, F., Chuwardi, C., Wuvanka, Y., & Huandra, E. (2025). Analsis Sentimen Churn Pelanggan dalam Layanan Streaming NETFLIX di X Menggunakan Metode IndoBERT. JDMIS: Journal of Data Mining and Information Systems, 3(2), 77–85. https://doi.org/10.54259/jdmis.v3i2.4281

Issue

Vol. 3 No. 2 (2025): August 2025

Section

Articles

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Copyright (c) 2025 Farencia Levis, Cindy Chuwardi, Yoshe Wuvanka, Eveleen Huandra

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