Teknokris
Vol 26 No 1 (2023): Jurnal Teknokris Edisi Juni

ANALISIS SENTIMEN TERHADAP PILPRES 2024 BERDASARKAN OPINI DARI TWITTER MENGGUNAKAN NAÏVE BAYES DAN SVM

Tamara Rosyida (Universitas Krisnadwipayana)
Harjono Padmono putro (Universitas Krisnadwipayana)
Herry Wahyono (Universitas Krisnadwipayana)

Article Info

Publish Date
06 Jun 2023

Abstract

Ahead of the Presidential Election, although it will run for about two years in the future, the large number of public opinion tweets about the 2024 Presidential Election on Twitter has caused positive and negative, from the data collection can be used as material for analysis. Naïve Bayes algorithm and the Support Vector Machine aims to determine the accuracy, precision, and recall values of the classification of positive or negative tweets. The method used is a qualitative method, the data taken amounted to 1606 datasets during April and May 2022. Result of RapidMiner 9.10 Tools, SVM Algorithm gets higher results by having an accuracy value of 98.43%, precision 97.15%, and recall 99.71%, Naïve Bayes algorithm has an accuracy value of 96.63%, precision 94.30%, and recall 98.90%. Based on the results of tweets that have elements of rejection of the 2024 Presidential Election, it is hoped that the public will not be able to happen

Copyrights © 2023




Citation Download
RIS
EndNote, Reference Manager, ProCite
BibTex
Latex, Jabref
Original Source
Download Original
Google Scholar
Check in Google Scholar
Journal Info
Teknokris
Website

Abbrev

teknokris

Publisher

Universitas Krisnadwipayana

Subject

Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mechanical Engineering

Description

Karya Ilmiah untuk mahasiswa dan dosen pada bidang Teknik Mesin, Teknik Elektro, Teknik Industri, Teknik Informatika, Teknik Sipil, Perencanaan Wilayah dan Kota, Arsitektur dan Sistem Informasi terbit setahun dua kali, setiap Juni dan ...