Proceedings of the First Mandalika International Multi-Conference on Science and Engineering 2022, MIMSE 2022 (Informatics and Computer Science) (MIMSE-I-C-2022)

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Utilizing Random Forest Algorithm for Sentiment Prediction Based on Twitter Data

Authors
Iwan Setiawan1, Agung Mulyo Widodo2, Mosiur Rahaman3, Tugiman4, Muhammad Abdullah Hadi2, Nizirwan Anwar2, *, Muhammad Bahrul Ulum2, Erry Yudhya Mulyani2, Nixon Erzed2
1Nusa Putra University, Sukabumi, 43152, Indonesia
2Esa Unggul University, Jakarta, 11510, Indonesia
3Asia University, Taichung, 413, Taiwan
4Buddhi Dharma University, Tangerang, 15115, Indonesia
*Corresponding author. Email: nizirwan.anwar@esaunggul.ac.id
Corresponding Author
Nizirwan Anwar
Available Online 26 December 2022.
DOI
10.2991/978-94-6463-084-8_37How to use a DOI?
Keywords
Classification and Analysis of Sentiment; Random Forest Algorithm; Polarity Analysis; social media; Twitter
Abstract

Information sharing throughout the globe or universe has become a characteristic of social media. There has been a lot of research into the classification of sentiments. In this study, Twitter has been mined for unstructured GoFood Reviews data. It has been preprocessed to analyze the reviews’ sentiment with polarity analysis, feature extraction with TF-IDF, and supervised learning with random forest. From June 1, 2022, to June 30, 2022, a total of 28763 tweets with the keyword GoFood were retrieved from Twitter. The data is processed by the Python programming language utilizing NLTK, Sastrawi for the Indonesian language, Textblob, TF-IDF, Random Forest Classification, and other algorithms. Twitter is a nearly limitless source for classifying text. This algorithm takes roughly five minutes to compute.

Copyright
© 2022 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the First Mandalika International Multi-Conference on Science and Engineering 2022, MIMSE 2022 (Informatics and Computer Science) (MIMSE-I-C-2022)
Series
Advances in Computer Science Research
Publication Date
26 December 2022
ISBN
978-94-6463-084-8
ISSN
2352-538X
DOI
10.2991/978-94-6463-084-8_37How to use a DOI?
Copyright
© 2022 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Iwan Setiawan
AU  - Agung Mulyo Widodo
AU  - Mosiur Rahaman
AU  - Tugiman
AU  - Muhammad Abdullah Hadi
AU  - Nizirwan Anwar
AU  - Muhammad Bahrul Ulum
AU  - Erry Yudhya Mulyani
AU  - Nixon Erzed
PY  - 2022
DA  - 2022/12/26
TI  - Utilizing Random Forest Algorithm for Sentiment Prediction Based on Twitter Data
BT  - Proceedings of the First Mandalika International Multi-Conference on Science and Engineering 2022, MIMSE 2022 (Informatics and Computer Science) (MIMSE-I-C-2022)
PB  - Atlantis Press
SP  - 446
EP  - 456
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-084-8_37
DO  - 10.2991/978-94-6463-084-8_37
ID  - Setiawan2022
ER  -