Sentiment analysis of reviews related to Unesco Global Geopark (UGG) Ciletuh Palabuhanratu on google maps using the naive bayes algorithm

Ciletuh Geopark is part of the UNESCO Global Geopark Network. This study will analyze a tourist review of the Ciletuh Pelabuhan Ratu Geopark based on reviews on Google Maps. The author considers that user reviews really need to be taken into account because it is to find out the reviews of tourists who share their experiences. Reviews from tourists who have visited geoparks are the most important thing because these reviews can be used as information to be used as data. This research uses the Naïve Bayes Algorithm, because this algorithm is considered to have a high enough level of accuracy so that it can determine the Unesco Global Geopark (UGG) Ciletuh Pelabuhanratu tourist attraction that is often visited based on tourist reviews on Google Maps. Then the highest accuracy value of this research is Palangpang with an accuracy value of 98.61%, the second position is the Cisolok Geyser tourist attraction with an accuracy value of 94.44%, then the third position is the Ujung Genteng tourist attraction with an accuracy value of 98.36%, the fourth namely the Cikaso tourist attraction with an accuracy value of 98.36%, the fifth is the Citepus tourist attraction with an accuracy value of 97.22%, the sixth is the Manic Peak tourist attraction with an accuracy value of 96.92%, the seventh is the Sodong tourist attraction with an accuracy value of 95.83%, the eighth is the Cipanarikan tourist attraction with an accuracy value of 95.01%, the ninth is the Teletubis Hill tourist attraction with an accuracy value of 94.48%, and the last is the Cimarinjung tourist attraction with an accuracy value of 94.44%.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-01-09
DOI
https://doi.org/10.1051/bioconf/202414802014/pdf
Primary Topic
Wheat and Barley Genetics and Pathology
Type
article
Field-Weighted Citation Impact
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article

Sentiment analysis of reviews related to Unesco Global Geopark (UGG) Ciletuh Palabuhanratu on google maps using the naive bayes algorithm

Springer Link (Chiba Institute of Technology)
Wheat and Barley Genetics and Pathology
article

Sentiment analysis of reviews related to Unesco Global Geopark (UGG) Ciletuh Palabuhanratu on google maps using the naive bayes algorithm

article en

Abstract

Ciletuh Geopark is part of the UNESCO Global Geopark Network. This study will analyze a tourist review of the Ciletuh Pelabuhan Ratu Geopark based on reviews on Google Maps. The author considers that user reviews really need to be taken into account because it is to find out the reviews of tourists who share their experiences. Reviews from tourists who have visited geoparks are the most important thing because these reviews can be used as information to be used as data. This research uses the Naïve Bayes Algorithm, because this algorithm is considered to have a high enough level of accuracy so that it can determine the Unesco Global Geopark (UGG) Ciletuh Pelabuhanratu tourist attraction that is often visited based on tourist reviews on Google Maps. Then the highest accuracy value of this research is Palangpang with an accuracy value of 98.61%, the second position is the Cisolok Geyser tourist attraction with an accuracy value of 94.44%, then the third position is the Ujung Genteng tourist attraction with an accuracy value of 98.36%, the fourth namely the Cikaso tourist attraction with an accuracy value of 98.36%, the fifth is the Citepus tourist attraction with an accuracy value of 97.22%, the sixth is the Manic Peak tourist attraction with an accuracy value of 96.92%, the seventh is the Sodong tourist attraction with an accuracy value of 95.83%, the eighth is the Cipanarikan tourist attraction with an accuracy value of 95.01%, the ninth is the Teletubis Hill tourist attraction with an accuracy value of 94.48%, and the last is the Cimarinjung tourist attraction with an accuracy value of 94.44%.

Springer Link (Chiba Institute of Technology)
Openalex Percentile: Top 41%
Wheat and Barley Genetics and Pathology
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