Komparasi Algoritma Naïve Bayes Dan Support Vector Machine (SVM) Pada Analisis Sentimen Kebijakan Kemdikbudristek Mengenai Kuota Internet Selama Covid-19

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3ABJVSHNCN" target="_blank" >RIV/00216208:11320/23:BJVSHNCN - isvavai.cz</a>

Výsledek na webu

<a href="https://ejournal.unama.ac.id/index.php/processor/article/view/897" target="_blank" >https://ejournal.unama.ac.id/index.php/processor/article/view/897</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.33998/processor.2023.18.2.897" target="_blank" >10.33998/processor.2023.18.2.897</a>

Jazyk výsledku

ruština

Název v původním jazyce

Komparasi Algoritma Naïve Bayes Dan Support Vector Machine (SVM) Pada Analisis Sentimen Kebijakan Kemdikbudristek Mengenai Kuota Internet Selama Covid-19

Popis výsledku v původním jazyce

"Sentiment analysis is an activity that is used to analyze public opinion about an incident such as the Ministry of Education and Culture's internet assistance quota during the Covid-19 pandemic through one of the Twitter social media. Twitter is a microblogging platform that is used to write an opinion or opinion about an event that can be used as a source of data used. The Naïve Bayes method and Support Vector Machine (SVM) are methods with a Machine Learning approach that can be used to perform sentiment analysis on Kemdikbudristek policies regarding MoEC Quotas in the process of classifying a tweet based on its emotional level and knowing the accuracy comparison between the Naïve Bayes method and the Support Vector Machine ( SVM)."

Název v anglickém jazyce

Komparasi Algoritma Naïve Bayes Dan Support Vector Machine (SVM) Pada Analisis Sentimen Kebijakan Kemdikbudristek Mengenai Kuota Internet Selama Covid-19

Popis výsledku anglicky

"Sentiment analysis is an activity that is used to analyze public opinion about an incident such as the Ministry of Education and Culture's internet assistance quota during the Covid-19 pandemic through one of the Twitter social media. Twitter is a microblogging platform that is used to write an opinion or opinion about an event that can be used as a source of data used. The Naïve Bayes method and Support Vector Machine (SVM) are methods with a Machine Learning approach that can be used to perform sentiment analysis on Kemdikbudristek policies regarding MoEC Quotas in the process of classifying a tweet based on its emotional level and knowing the accuracy comparison between the Naïve Bayes method and the Support Vector Machine ( SVM)."

Druh

J_ost - Ostatní články v recenzovaných periodicích

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

—

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

"Jurnal PROCESSOR"

ISSN

1907-6738

e-ISSN

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Svazek periodika

18

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

RU - Ruská federace

Počet stran výsledku

9

Strana od-do

183-191

Kód UT WoS článku

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EID výsledku v databázi Scopus

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