KLASIFIKASI SENTIMEN ULASAN PENGGUNA APLIKASI PEDULILINDUNGI DI GOOGLE PLAY MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE DENGAN SELEKSI FITUR CHI-SQUARE
The government's efforts to reduce the spread of the corona virus outbreak which is increasingly widespread in almost every country in the world, including Indonesia, have been carried out. One of the efforts that have been made by utilizing existing technology at this time is to create an appl...
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2022-07-02.
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| 100 | 1 | 0 | |a Cindy Chairunnisa, , |e author |
| 245 | 0 | 0 | |a KLASIFIKASI SENTIMEN ULASAN PENGGUNA APLIKASI PEDULILINDUNGI DI GOOGLE PLAY MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE DENGAN SELEKSI FITUR CHI-SQUARE |
| 260 | |c 2022-07-02. | ||
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| 500 | |a http://repository.upnvj.ac.id/19619/10/LAMPIRAN.pdf | ||
| 500 | |a http://repository.upnvj.ac.id/19619/11/HASIL%20PLAGIARISME.pdf | ||
| 500 | |a http://repository.upnvj.ac.id/19619/12/ARTIKEL%20KI.pdf | ||
| 520 | |a The government's efforts to reduce the spread of the corona virus outbreak which is increasingly widespread in almost every country in the world, including Indonesia, have been carried out. One of the efforts that have been made by utilizing existing technology at this time is to create an application called PeduliLindungi. This application aims to track and monitor the location of the spread of the corona virus so that it can reduce corona cases in Indonesia. Many reviews have been given by the community to this application, both in the form of criticism and satisfaction. However, to find out all the reviews given is not easy. Therefore, the research was conducted with the aim of knowing the results of public sentiment towards the PeduliLindung application. Sentiment analysis was carried out by classifying reviews into positive reviews and negative reviews using the Support Vector Machine algorithm by selecting the chi-square feature. Reviews Data collection is done by scrapping on google play using the Python programming language. The results of the sentiment classification of the PeduliLindung application resulted in good performance and resulted in a score of 93%, recall of 86%, precision of 98%, specificity of 98% and f1-score of 92%. | ||
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