Twitter user sentiment analysis for RUU Omnibus Law using convolutional neural network

Zulfikar, Wildan Budiawan and Dauni, Popon and Ramdhani, Muhammad Ali and Suryapratama, Dimas Ramdhani and Jumadi, Jumadi and Fuadi, Rifqi Syamsul (2022) Twitter user sentiment analysis for RUU Omnibus Law using convolutional neural network. In: ICCED 2022.

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Abstract

The general function of social media is for online interaction with many people. Moreover, social media have functions for sharing information, discussion, and giving an opinion media about some topics that a lot of people talk about, one of that media is Twitter. An atopic will show many opinions and different responses from everyone. This study was for making an analysis opinion from social media Twitter user about Rancangan Undang-Undang (RUU) Omnibuslaw topic using a Convolutional Neural Network method wich one of Deep Learning method. This study has been done a sentiment analysis with opinion data from many different people through the tweet they making, Preprocessing and weighting are done using Word2vec which give 84% result accuracy of an algorithm from 10-time testing. Based on 2.820 tweet data, the result is 1.320 data of positive sentiment, and 1.500 data of negative response for the RUU Omnibuslaw topic in Indonesia.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Convolutional Neural Network (CNN); RUU; Omnibuslaw; Sentiment Analysis; Twitter
Subjects: Data Processing, Computer Science
Divisions: Fakultas Sains dan Teknologi > Program Studi Teknik Informatika
Depositing User: Wildan Budiawan Zulfikar
Date Deposited: 02 May 2023 03:44
Last Modified: 02 May 2023 03:44
URI: https://digilib.uinsgd.ac.id/id/eprint/67085

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