Sentiment analysis on the place of interest in Malaysia
This study focuses on utilizing machine learning methods for sentiment analysis to identify positive and negative comments regarding Malaysian Places of Interest. The data was collected from Twitter using social media monitoring software and organized into tables. Pre-processing techniques and Natur...
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| Format: | Article |
| Language: | English |
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Semarak Ilmu Publishing
2025
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| Online Access: | http://umpir.ump.edu.my/id/eprint/41344/1/Sentiment%20Analysis%20on%20The%20Place%20of%20Interest%20in%20Malaysia.pdf |
| _version_ | 1811138406188580864 |
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| author | Qiryn Adriana, Khairul Zaman Wan Nur Syahidah, Wan Yusoff Qistina Batrisyia, Azman Shah |
| author_facet | Qiryn Adriana, Khairul Zaman Wan Nur Syahidah, Wan Yusoff Qistina Batrisyia, Azman Shah |
| author_sort | Qiryn Adriana, Khairul Zaman |
| collection | UMP |
| description | This study focuses on utilizing machine learning methods for sentiment analysis to identify positive and negative comments regarding Malaysian Places of Interest. The data was collected from Twitter using social media monitoring software and organized into tables. Pre-processing techniques and Natural Language Processing (NLP) methods were applied to handle missing values and prepare the text data for analysis. The dataset was then split into training and testing sets, and three supervised learning algorithms which are Support Vector Machine, Random Forest, and Naive Bayes were employed to evaluate the sentiment analysis models. The performance of each model was compared, and it was found that Support Vector Machine achieved the highest accuracy, recall score, F1 score, and precision score. This study demonstrates the potential to extend sentiment analysis to analyze sentiments expressed in texts written in the Malay language by utilizing the Malaya corpus. Additionally, visual dashboards can be created to present the findings and provide recommendations based on the insights gathered from the sentiment analysis of Malaysian Places of Interest feedback. |
| first_indexed | 2024-09-25T03:49:41Z |
| format | Article |
| id | UMPir41344 |
| institution | Universiti Malaysia Pahang |
| language | English |
| last_indexed | 2024-09-25T03:49:41Z |
| publishDate | 2025 |
| publisher | Semarak Ilmu Publishing |
| record_format | dspace |
| spelling | UMPir413442024-07-01T01:10:02Z http://umpir.ump.edu.my/id/eprint/41344/ Sentiment analysis on the place of interest in Malaysia Qiryn Adriana, Khairul Zaman Wan Nur Syahidah, Wan Yusoff Qistina Batrisyia, Azman Shah Q Science (General) QA Mathematics This study focuses on utilizing machine learning methods for sentiment analysis to identify positive and negative comments regarding Malaysian Places of Interest. The data was collected from Twitter using social media monitoring software and organized into tables. Pre-processing techniques and Natural Language Processing (NLP) methods were applied to handle missing values and prepare the text data for analysis. The dataset was then split into training and testing sets, and three supervised learning algorithms which are Support Vector Machine, Random Forest, and Naive Bayes were employed to evaluate the sentiment analysis models. The performance of each model was compared, and it was found that Support Vector Machine achieved the highest accuracy, recall score, F1 score, and precision score. This study demonstrates the potential to extend sentiment analysis to analyze sentiments expressed in texts written in the Malay language by utilizing the Malaya corpus. Additionally, visual dashboards can be created to present the findings and provide recommendations based on the insights gathered from the sentiment analysis of Malaysian Places of Interest feedback. Semarak Ilmu Publishing 2025-01 Article PeerReviewed pdf en cc_by_nc_4 http://umpir.ump.edu.my/id/eprint/41344/1/Sentiment%20Analysis%20on%20The%20Place%20of%20Interest%20in%20Malaysia.pdf Qiryn Adriana, Khairul Zaman and Wan Nur Syahidah, Wan Yusoff and Qistina Batrisyia, Azman Shah (2025) Sentiment analysis on the place of interest in Malaysia. Journal of Advanced Research in Applied Sciences and Engineering Technology, 43 (1). pp. 54-65. ISSN 2462-1943. (Published) https://doi.org/10.37934/araset.43.1.5465 https://doi.org/10.37934/araset.43.1.5465 |
| spellingShingle | Q Science (General) QA Mathematics Qiryn Adriana, Khairul Zaman Wan Nur Syahidah, Wan Yusoff Qistina Batrisyia, Azman Shah Sentiment analysis on the place of interest in Malaysia |
| title | Sentiment analysis on the place of interest in Malaysia |
| title_full | Sentiment analysis on the place of interest in Malaysia |
| title_fullStr | Sentiment analysis on the place of interest in Malaysia |
| title_full_unstemmed | Sentiment analysis on the place of interest in Malaysia |
| title_short | Sentiment analysis on the place of interest in Malaysia |
| title_sort | sentiment analysis on the place of interest in malaysia |
| topic | Q Science (General) QA Mathematics |
| url | http://umpir.ump.edu.my/id/eprint/41344/1/Sentiment%20Analysis%20on%20The%20Place%20of%20Interest%20in%20Malaysia.pdf |
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