Proceedings of the Conference on SDGs Transformation through the Creative Economy: Encouraging Innovation and Sustainability (TCEEIS 2023)

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Sentiment Analysis Based on Review of Puncak B29 Lumajang using Backpropagation Neural Network

Authors
Fadhel Akhmad Hizham1, *, Cahyasari Kartika Murni2
1Informatics Department, Institut Teknologi Dan Bisnis Widya Gama Lumajang, Lumajang, Indonesia
2Informatics Department, Institut Teknologi Dan Bisnis Widya Gama Lumajang, Lumajang, Indonesia
*Corresponding author. Email: hizhamfadhel@gmail.com
Corresponding Author
Fadhel Akhmad Hizham
Available Online 11 January 2024.
DOI
10.2991/978-94-6463-346-7_39How to use a DOI?
Keywords
—Sentiment Analysis; Text Mining; Puncak B29; Backpropagation Neural Network
Abstract

Sentiment analysis is a method that applies the concept of text mining to provide a classification that has positive, negative or neutral polarity for each sentence or document. The problem formulation carried out in this research is the role of sentiment analysis in analyzing reviews of the Puncak B29 Lumajang tourist attraction based on user comments on Google Maps. This research was carried out in 3 stages, starting with data collection in the form of a review of the Google Maps application which was carried out by scrapping data, carrying out text preprocessing, including case folding, tokenizing, stopwords, and stemming and categorizing each review according to sentiment using the Backpropagatin Neural Network (BNN) classification method. Sentiment classification based on Puncak B29 reviews on Google Maps using Backpropagation Neural Network has the best accuracy, recall and F1-score evaluation results for a total of 50 iterations, each with an average value of 97.33%, 100.00% and 98.47%. Meanwhile, the best precision value for the number of iterations is 10 iterations, which has an average value of 99.72%. From this description, it can be concluded that the evaluation value will get better along with the number of iterations carried out throughout the classification process.

Copyright
© 2023 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 Conference on SDGs Transformation through the Creative Economy: Encouraging Innovation and Sustainability (TCEEIS 2023)
Series
Advances in Economics, Business and Management Research
Publication Date
11 January 2024
ISBN
978-94-6463-346-7
ISSN
2352-5428
DOI
10.2991/978-94-6463-346-7_39How to use a DOI?
Copyright
© 2023 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  - Fadhel Akhmad Hizham
AU  - Cahyasari Kartika Murni
PY  - 2024
DA  - 2024/01/11
TI  - Sentiment Analysis Based on Review of Puncak B29 Lumajang using Backpropagation Neural Network
BT  - Proceedings of the Conference on SDGs Transformation through the Creative Economy: Encouraging Innovation and Sustainability (TCEEIS 2023)
PB  - Atlantis Press
SP  - 210
EP  - 214
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-346-7_39
DO  - 10.2991/978-94-6463-346-7_39
ID  - Hizham2024
ER  -