Faza Abdillah Gunawan Soerawinata, . (2022) ANALISIS SENTIMEN PENGGUNA ANDROID TERHADAP APLIKASI PEDULILINDUNGI DENGAN MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
![[img]](http://repository.upnvj.ac.id/style/images/fileicons/text.png) |
Text
ABSTRAK.pdf Download (46kB) |
|
Text
AWAL.pdf Download (945kB) |
|
Text
BAB 1.pdf Download (127kB) |
|
Text
BAB 2.pdf Restricted to Repository UPNVJ Only Download (278kB) |
|
Text
BAB 3.pdf Restricted to Repository UPNVJ Only Download (86kB) |
|
Text
BAB 4.pdf Restricted to Repository UPNVJ Only Download (737kB) |
|
Text
BAB 5.pdf Download (46kB) |
|
Text
DAFTAR PUSTAKA.pdf Download (115kB) |
|
Text
RIWAYAT HIDUP.pdf Restricted to Repository UPNVJ Only Download (57kB) |
|
Text
LAMPIRAN.pdf Restricted to Repository UPNVJ Only Download (732kB) |
|
Text
HASIL PLAGIARISME.pdf Restricted to Repository staff only Download (1MB) |
|
Text
ARTIKEL KI.pdf Restricted to Repository staff only Download (388kB) |
Abstract
In order to reduce the spread of COVID-19 virus government worked together with Komite Penanganan COVID-19 dan Pemulihan Ekonomi Nasional in short KPCPEN, Ministry of Health, and Ministry of BUMN have developed PeduliLindungi app to help perform tracing, tracking, warning and fencing for the Indonesian people in their trip outside and also coming to a particular event. Certainly, this program needs the enthusiasm from the people to be successful in the implementation that one of which is measured by the rating that people gave using the review feature in the related app. This research conducted to analyze people enthusiasm by doing sentiment analysis based on the review given to the PeduliLindungi app. The sentiment analysis was done by extracting data using scrapping technique in the Google Play website, after 1001 data was collected we continued by doing preprocess data, data labelling, feature extraction, and split data. The outcome data then implemented to the Support Vector Machine algorithm for classification based on its review and target sentiment given. Based on the model made, the best accuracy obtained is 85,5%. The purpose of this research is to measure the people enthusiasm on the app and gave recommendation for the improvement of the app.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No.Panggil: 1810512118] [Pembimbing 1: Ermatita] [Pembimbing 2: Rio Wirawan] [Penguji 1: Iin Ernawati] [Penguji 2: Ria Asriratma] |
| Uncontrolled Keywords: | Sentiment Analysis, Review, Classification, Support Vector Machine |
| Subjects: | T Technology > T Technology (General) |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Sistem Informasi (S1) |
| Depositing User: | Faza Abdillah Gunawan Soerawinata |
| Date Deposited: | 04 Aug 2022 03:42 |
| Last Modified: | 04 Aug 2022 03:42 |
| URI: | http://repository.upnvj.ac.id/id/eprint/19762 |
Actions (login required)
 |
View Item |