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All Journal INFORMATIKA J-ENSITEC (Journal of Engineering and Sustainable Technology)
Marvin Donald Richardo Aronggear
Unknown Affiliation
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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ANALISIS SENTIMENT KOMENTAR VIDEO YOUTUBE “EPIC RAP BATTLE OF PRESIDENCY 2024” MENGGUNAKAN ALGORITMA NAÏVE BAYES & SVM Gavin Berylian Josepto; Rafif Dhia Yusrana; Marvin Donald Richardo Aronggear; Viktor Handrianus Pranatawijaya; Ressa Priskila
J-ENSITEC Vol. 10 No. 02 (2024): June 2024
Publisher : Universitas Majalengka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31949/jensitec.v10i02.9210

Abstract

Sentiment analysis of YouTube video recordings has become important in this increasingly technologically advanced era to understand users' reactions and opinions on various topics, including politics. Rapfight videos, especially those related to the presidential election, are one type of content that often attracts attention. This research uses the Naïve Bayes algorithm to assess the sentiment of comments on the video "Epic Rap Battle of Presidency 2024" on the YouTube site. The algorithms used in this research are Naïve Bayes Classifier and Support Vector Machine (SVM). There are five processes in this research, namely collecting YouTube comment data, preprocessing, labeling, classification, implementation and testing. From 3650 comment data on YouTube regarding the video "Epic Rap Battle of Presidency 2024" based on the results of the analysis, it was found that 31% of the comments were positive, 7% of the comments were negative and 62% of the comments were neutral. The accuracy results using the Naïve Bayes Classifier algorithm were 84.82% and the accuracy results using the Support Vector Machine (SVM) algorithm got the best results at 93.3%.
ANALISIS IMPLEMENTASI COMPUTING CURRICULA 2020 DALAM PENDIDIKAN ILMU KOMPUTER Gavin Berylian Josepto; Thomas Zugildo Magnus; Marvin Donald Richardo Aronggear; Jadiaman Parhusip
Informatika: Jurnal Teknik Informatika dan Multimedia Vol. 4 No. 2 (2024): Oktober : JURNAL TEKNIK INFORMATIKA DAN MULTIMEDIA
Publisher : LPPM Politeknik Pratama Kendal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/informatika.v4i2.822

Abstract

Computing Curricula 2020 (CC 2020), published by ACM and IEEE, provides the latest guidelines for developing computer science education curricula worldwide. This journal analyzes the implementation and impact of Computing Curricula 2020 on computer science education. Special emphasis is placed on curriculum structure, the teaching of technical and non-technical skills, and adaptation to the evolving needs of the technology industry. Using data contained in Computing Curricula 2020, this journal explores how the curriculum serves as a guide to produce competent graduates who are industry-ready and understand the social and ethical implications of technology.
Co-Authors Gavin Berylian Josepto Jadiaman Parhusip, Jadiaman Rafif Dhia Yusrana Ressa Priskila Thomas Zugildo Magnus Viktor Handrianus Pranatawijaya