2020
DOI: 10.1088/1742-6596/1567/3/032024
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Twitter text mining for sentiment analysis on government’s response to forest fires with vader lexicon polarity detection and k-nearest neighbor algorithm

Abstract: Opinions about the government’s response to forest fires have drawn many opinions from the community. One way for people to express their opinions is to use social media Twitter. This study conducted a sentiment analysis process on the government’s response to handling forest fires in Indonesia in 2019 with data sources from Twitter. The analysis was carried out on 6325 datasets written on Twitter on September 20, 2019, and then through the process of pre-processing, automating labeling and classification. The… Show more

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Cited by 31 publications
(33 citation statements)
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“…Variable data 0 means that it is not bankrupt and vice versa in data variable 1 indicates bankruptcy. Data pre-processing means normalizing data sets that do not support the analysis process [47], [55]. Data that do not support the analysis process are repetitive data, blank data and abnormal data.…”
Section: Methodsmentioning
confidence: 99%
“…Variable data 0 means that it is not bankrupt and vice versa in data variable 1 indicates bankruptcy. Data pre-processing means normalizing data sets that do not support the analysis process [47], [55]. Data that do not support the analysis process are repetitive data, blank data and abnormal data.…”
Section: Methodsmentioning
confidence: 99%
“…Related studies deal with "sentiment analysis". Mustaqim et al [26] studied public feelings (the "sentiment analysis") about the Indonesian government's response to handling forest fires in 2019 by using a semi-automated labeling and classification scheme. Mustaquim et al state that sentiment analysis provides a way for businesspeople and academic institutions to better understand community thinking.…”
Section: Literature Review 21 Use Of Social Media In Early Detection Of and Warning Of Disaster Eventsmentioning
confidence: 99%
“…However, such an analysis is beyond the scope of the current work. One intriguing angle would be the development of semi-automatic sentiment analysis as suggested recently by Mustaqim et al [26], but one which would also provide satellite and meteorological data.…”
Section: Empirical Analysis Of Social Media Responsementioning
confidence: 99%
“…Keterangan : = varian ke i = rata-rata nilai i ( ) = nilai atribut ke i sampai ke j = jumlah sampel Selanjutnya dilakukan proses Pre-Processing yang dibagi menjadi case folding yang berfungsi untuk merubah semua kata pada dataset menjadi huruf kecil [9]. Tokenisize berguna untuk membagi setiap kata manjadi token.…”
Section: Gambar 1 Tahapan Penelitianunclassified
“…Stopword removal berfungsi untuk menghilangkan titik, koma, tanda baca dan juga menghilangkan kata-kata dasar yang tidak memiliki makna [10]. Lalu steamming untuk menghilangkan kata imbuhan menjadi kata dasar agar semua kata dasar yang sama tapi memiliki imbuhan berbeda bisa menjadi sama [9]. Translate berguna untuk mengganti kata yang berbahasa asing kedalam bahasa indonesia [4].…”
Section: Gambar 1 Tahapan Penelitianunclassified