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All Journal Teknik: Jurnal Ilmu Teknik dan Informatika J-ENSITEC (Journal of Engineering and Sustainable Technology)
Rafif Dhia Yusrana
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Civil Engineering, Building, Construction & Architecture Computer Science & IT 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 Distribusi Rata-Rata Anggaran Pendapatan APBN 2024 Di Tingkat Provinsi Gavin Berylian Josepto; Marvin Donald Richardo Aronggear; Rafif Dhia Yusrana; Jadiaman Parhusip
Teknik: Jurnal Ilmu Teknik dan Informatika Vol. 4 No. 2 (2024): Oktober : Teknik: Jurnal Ilmu Teknik dan Informatika
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi - Studi Ekonomi Modern

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/teknik.v4i2.577

Abstract

Penelitian ini menganalisis distribusi dan variasi alokasi anggaran APBN 2024 di tingkat provinsi di Indonesia menggunakan pendekatan statistik deskriptif. Data diolah untuk menghitung rata-rata dan simpangan baku anggaran setiap provinsi guna mengidentifikasi ketimpangan alokasi. Hasil dari penelitian ini menunjukkan adanya ketimpangan signifikan, dengan DKI Jakarta memiliki rata-rata anggaran tertinggi sebesar Rp. 2,4 triliun, sedangkan provinsi lain seperti Gorontalo dan Maluku Utara berada jauh di bawahnya. Selain itu juga, ketimpangan internal juga ditemukan, terutama di wilayah Papua. Temuan ini mengindikasikan perlunya kebijakan redistribusi anggaran yang lebih merata untuk mendukung pembangunan yang merata di seluruh wilayah Indonesia.
Co-Authors Gavin Berylian Josepto Jadiaman Parhusip, Jadiaman Marvin Donald Richardo Aronggear Ressa Priskila Viktor Handrianus Pranatawijaya