Implementation of Convolutional Neural Network Algorithm in Sentiment Analysis on User Reviews Of MySAPK Application

• Author(s): Vanessia Putriadiva ; Marliza Ganefi Gumay
• Paper ID: 1703301
• Page: 459-462
• Published Date: 30-03-2022
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 5 Issue 9 March-2022

Abstract

BKN launched the MySAPK application to independently update personal data and history. Sentiment analysis was conducted to evaluate the quality and performance of the MySAPK application. The data used is a user review of the MySAPK application using the Convolutional Neural Network (CNN) algorithm.The research method consists of data collection, labeling, preprocessing, processing, testing, and evaluation. The Convolutional Neural Network (CNN) algorithm produces an accuracy rate of 90% in the testing process, with positive sentiments from its users.

Keywords

Sentiment Analysis, Convolutional Neural Network (CNN), MySAPK.

Citations

IRE Journals:
Vanessia Putriadiva , Marliza Ganefi Gumay "Implementation of Convolutional Neural Network Algorithm in Sentiment Analysis on User Reviews Of MySAPK Application" Iconic Research And Engineering Journals Volume 5 Issue 9 2022 Page 459-462

IEEE:
Vanessia Putriadiva , Marliza Ganefi Gumay "Implementation of Convolutional Neural Network Algorithm in Sentiment Analysis on User Reviews Of MySAPK Application" Iconic Research And Engineering Journals, 5(9)