The Right Sentiment Analysis Method of Indonesian Tourism in Social Media Twitter

Steven, Cristian; Wella, Wella

doi:10.31937/ijnmt.v7i2.1732

Cited by 10 publications

(5 citation statements)

References 12 publications

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“…Penelitian ini melakukan text mining (Singh et al, 2021) pada suatu komentar mengenai Citayam Fashion Week pada media sosial twitter yang sering di gunakan untuk bersosialisasi antar pengguna sebagai bentuk luapan opini pada media social. (Steven & Wella, 2020) (Lestari et al, 2017)(Destitus et al, 2020. Karena banyaknya luapan opini pada media social, hal ini dapat dijadikan sebagai acuan dasar dalam menanalisa sentiment pada masing masing luapan opini masyarakat terhadap suatu topik yang saat itu sedang menjadi pembicaraan yang cukup menarik.…”

Section: Pendahuluanunclassified

Sentiment Analysis Public Opinion of CFW (Citayam Fashion Week) on Social Media Twitter Using Naïve Bayes Classifier

Permana

Putra²

2023

JIKA

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The increasing interest of young people in Indonesia towards local fashion brands is an opportunity to bring the Indonesian fashion industry to the international market, this has triggered people's desire to become a fashion designer. This fashion development has made many teenagers able to express their hobbies, one of which is on public roads in the Sudirman area, or more commonly called Citayam Fashion Week (CFW). CFW is very much a phenomenon in the middle of 2022, but of course this reaps a lot of opinions, some react positively, some even criticize, This is the area where the study needs to be done in order to examine the sentiment on Twitter and other social media, The research methodology consists of several stages, namely, data collection, praprocessing, data classification, and conclusions and suggestions the method used is naïve Bayes classifier with evaluation using a confusion matrix, with an accuracy of 84%. This research is useful for extracting opinions from Twitter social media regarding CFW with the results of more positive responses to CFW.

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Section: Pendahuluanunclassified

Sentiment Analysis Public Opinion of CFW (Citayam Fashion Week) on Social Media Twitter Using Naïve Bayes Classifier

Permana

Putra²

2023

JIKA

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“…Analisis Sentimen atau sering juga disebut penambangan opini adalah studi komputasi dari pendapat, penilaian, dan emosi orang melalui entitas, peristiwa, dan atribut yang dimiliki [6]. Berdasarkan studi yang telah dilakukan sebelumnya [6] memaparkan temuan terdahulu [7], Analisis sentimen telah menjadi topik yang populer untuk digunakan karena analisis sentimen dapat diterapkan di banyak sektor industri, termasuk industri pariwisata. Sektor pariwisata di Indonesia sendiri selalu mengalami perbaikan setiap tahunnya dan sektor pariwisata ini kini menduduki peringkat ke-42 dunia [8].…”

Section: Pendahuluanunclassified

Sentiment Analysis Untuk Review Destinasi Wisata Unggulan Gunung Kidul Menggunakan Metode Lexicon Dan Pivot

Larasati

Nabilla²,

Haryanto³

2022

IJUBI

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Social media in providing freedom of access to information has a rapid effect on tourist destinations in Indonesia. A tweet may also contain information or conditions about tourist destinations that they will or have visited, such as visitor experiences in traveling, visitors' opinions of tourist attractions, and other tourist attractions. The condition of tourism globally, especially in the Gunungkidul area after the Covid-19 pandemic, has experienced a significant decline. This condition motivated researchers to conduct research with the aim of contributing to post-Covid-19 tourism development, in particular by conducting a sentiment analysis of comments by tourists visiting tourist areas in Gunungkidul Regency. Sentiment analysis is the process of using text analytics to derive various data sources from the internet and various social media platforms. Comment data obtained through social media Twitter. This classification is used to find out how comments about tourist attractions in Gunungkidul are. Lexicon based and pivoting are methods used to classify public opinion into three classes, namely positive, negative and neutral sentiments. This method is used to classify the results of community comment data written on the form of community satisfaction with tourism in Gunungkidul. This study aims to find out how people's opinions regarding tourism in Gunungkidul during the Covid-19 pandemic took place. The results of this study are used to determine the classification of community commentary data so that services can be easily developed through comments given by the public. The results of the sentiment analysis show that there are 51% positive emotion categories, 1% negative and 48% neutral.

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“…Sentiment analysis (SA), also known as opinion mining is the computation of people"s opinions, judgments and emotions through entities, events and attributes held by the users [4]. Sentiment analysis or opinion mining uses natural language processing and text analytics to locate and extract subjective information from source materials.…”

Section: Introductionmentioning

confidence: 99%

Post Pandemic Tourism: Sentiment Analysis using Support Vector Machine Based on TikTok Data

Sabri,

Subki,

Bahrin

et al. 2024

IJACSA

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The tourism industry is one of the hard hit businesses during the Covid-19 pandemic and has been struggling for backup ever since. However, nowadays the industry has started to bloom again with the lifting of all of the restrictions of Covid-19. This research aims to analyze the sentiments of the tourists using the Support Vector Machine (SVM) algorithm to know their views on the tourist spots after the pandemic. The scope of the research covers the state of Terengganu which is popularly known for its islands and unique culture on the east coast of Malaysia. TikTok data has been used as the source of data as social media currently has become one of the top mediums for reviewing, selling and promoting products and services. The objective of the research is to explore the SVM algorithm in the sentiment classification of tourist spots in Terengganu. This research is expected to help the Tourism Terengganu to improve their tourist spots and their services. The phases of the research include collecting data from TikTok, data pre-processing, data labelling, feature extraction, model creation using SVM, graphical user interface development and performance evaluation. The evaluation results showed that the performance of the SVM classifier model was good and reliable, with 90.68% accuracy. The future work would be collecting more data from TikTok regularly to further improve the accuracy of the algorithm.

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The Right Sentiment Analysis Method of Indonesian Tourism in Social Media Twitter

Cited by 10 publications

References 12 publications

Sentiment Analysis Public Opinion of CFW (Citayam Fashion Week) on Social Media Twitter Using Naïve Bayes Classifier

Sentiment Analysis Public Opinion of CFW (Citayam Fashion Week) on Social Media Twitter Using Naïve Bayes Classifier

Sentiment Analysis Untuk Review Destinasi Wisata Unggulan Gunung Kidul Menggunakan Metode Lexicon Dan Pivot

Post Pandemic Tourism: Sentiment Analysis using Support Vector Machine Based on TikTok Data

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