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Tamara Rosyida
Universitas Krisnadwipayana
Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Journal : Teknokris

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ANALISIS SENTIMEN TERHADAP PILPRES 2024 BERDASARKAN OPINI DARI TWITTER MENGGUNAKAN NAÏVE BAYES DAN SVM Tamara Rosyida; Harjono Padmono putro; Herry Wahyono
TEKNOKRIS Vol 26 No 1 (2023): Jurnal Teknokris Edisi Juni
Publisher : Fakultas Teknik Unkris Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61488/teknokris.v26i1.245

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
Co-Authors Harjono Padmono Putro Herry Wahyono