Sentiment Analysis of YouTube Comments on Indonesia’s Performance in 2026 World Cup Qualifiers Using Naive Bayes

Dihin Muriyatmoko; Aziz Musthafa; Yusuf Al Banna

doi:10.61132/prosemnasproit.v2i2.196

Authors

Dihin Muriyatmoko Universitas Darussalam Gontor
Aziz Musthafa Universitas Darussalam Gontor
Yusuf Al Banna Universitas Darussalam Gontor

DOI:

https://doi.org/10.61132/prosemnasproit.v2i2.196

Keywords:

Naive Bayes, public opinion, sentiment analysis, sports performance, YouTube comments

Abstract

Sentiment analysis on social media is widely used to represent public perceptions of sports performance, particularly in international competitions. This study aims to analyze the sentiment of YouTube user comments regarding the performance of the Indonesian National Football Team during the FIFA World Cup 2026 Asian Qualifiers. The data were collected from user comments on videos related to the matches and analyzed using a machine learning–based sentiment analysis approach. Sentiment classification was performed using the Naive Bayes algorithm. The results indicate that the proposed approach is able to effectively identify public sentiment toward the national team’s performance during the qualification matches. The findings of this study are expected to provide insights into public perceptions and contribute to sentiment analysis research in the field of sports.

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