PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic
Vol. 13 No. 1 (2025): Maret 2025

Sentiment Analysis of YouTube Comments Using Machine Learning Models

Susanti, Erma (Unknown)
Maimunah, Maimunah (Unknown)
Nugroho, Setiya (Unknown)



Article Info

Publish Date
31 Mar 2025

Abstract

The documentary video “115. You Are Human Too” from the #MenjadiManusia YouTube channel raises mental health issues with an empathic narrative approach. Social media plays a role in shaping public understanding, but opinions vary from support to stigma. This study analyzed the sentiment of 1,350 comments on the video using the YouTube API. Comments were classified into positive, negative and neutral sentiments using the IndoBERT model after preprocessing. Four machine learning algorithms were compared: Naïve Bayes, Random Forest, Support Vector Machine (SVM), and Extra Trees. Results showed that SVM had the highest accuracy (79.67%), followed by Random Forest (78.02%), Extra Trees (75.27%), and Naïve Bayes (70.33%). This analysis reveals patterns of public opinion on mental health, which can serve as a reference for academics, health practitioners, and policy makers in designing more effective communication strategies. In addition, this research is expected to increase public understanding of mental health and encourage more inclusive discussions on social media.

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Journal Info

Abbrev

piksel

Publisher

Subject

Computer Science & IT Decision Sciences, Operations Research & Management

Description

Jurnal PIKSEL diterbitkan oleh Universitas Islam 45 Bekasi untuk mewadahi hasil penelitian di bidang komputer dan informatika. Jurnal ini pertama kali diterbitkan pada tahun 2013 dengan masa terbit 2 kali dalam setahun yaitu pada bulan Januari dan September. Mulai tahun 2014, Jurnal PIKSEL mengalami ...