Infotech Journal
Vol. 8 No. 2 (2022)

KLASIFIKASI SENTIMEN PERGELARAN MOTOGP DI INDONESIA MENGGUNAKAN ALGORITMA CORRELATED NAÏVE BAYES CLASIFIER

RIDWAN INDRANSYAH (Program Studi Informatika, Fakultas Sains dan Informatika, Universitas Jenderal Achmad Yani)
Yulison Herry Chrisnanto (Unknown)
Puspita Nurul Sabrina (Unknown)



Article Info

Publish Date
26 Oct 2022

Abstract

Knowing the public's sentiment towards the international MotoGP event which has been held in Indonesia in 2022 is very necessary because the role of the community is very influential in the implementation and public interest in visiting an international event is still few and difficult because the information is still limited. Tweets, comments, reviews, and opinions of people using social media play an important role in determining whether a particular population is satisfied with products, performances, and services. The method used in this study is the Correlated Naïve Bayes Classifier (CNBC). The Correlated Naive Bayes Classifier (CNBC) method recalculates the correlation value for each attribute of the dataset to that class. There are several processes carried out in this study including data acquisition, data labeling, data preprocessing, feature extraction, classifying data using the Correlated Naive Bayes Classifier (CNBC) method, visualizing data, and finally evaluating the results. This study resulted in an accuracy of 82%.

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Journal Info

Abbrev

infotech

Publisher

Subject

Computer Science & IT

Description

Infotech Journal is a Scientific Paper published by the Informatics Study Program of the Faculty of Engineering, Majalengka University. The areas of competence covered by Infotech are Information Systems, Programming, Networks, Robotics, Artificial Intelligence and ...