Alfiyah Nur Indraini, . (2021) ANALISIS SENTIMEN TERHADAP PEMBELAJARAN DARING DI INDONESIA : Menggunakan Support Vector Machine (SVM). Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
Text
ABSTRAK.pdf Download (309kB) |
|
Text
AWAL.pdf Download (914kB) |
|
Text
BAB 1.pdf Download (339kB) |
|
Text
BAB 2.pdf Restricted to Repository UPNVJ Only Download (844kB) |
|
Text
BAB 3.pdf Restricted to Repository UPNVJ Only Download (450kB) |
|
Text
BAB 4.pdf Restricted to Repository UPNVJ Only Download (1MB) |
|
Text
BAB 5.pdf Download (428kB) |
|
Text
DAFTAR PUSTAKA.pdf Download (325kB) |
|
Text
RIWAYAT HIDUP.pdf Restricted to Repository UPNVJ Only Download (224kB) |
|
Text
LAMPIRAN.pdf Download (1MB) |
|
Text
ARTIKEL KI.pdf Download (777kB) |
Abstract
During this pandemic, a new policy was created in the world of education. The policy encourages students to carry out online learning for a long period of time. The new policy raises a lot of public opinion conveyed through social media. Twitter social media is used as a forum for opinions, one of which is about online learning. Therefore, this study will conduct a sentiment analysis on public opinion regarding online learning in Indonesia to provide information or evaluation of public opinion on Twitter social media. Sentiment analysis can be done by classifying public opinion into positive opinion and negative opinion with the Support Vector Machine (SVM) method. In classifying data, data labeling and data cleaning can be carried out first before going through the text preprocessing process, then the data is given a weight for each word with Term Frequency–Inverse Document Frequency (TF-IDF) which will be used as a feature after that the data is divided using a 10-fold cross. validation and classified by the Support Vector Machine (SVM) method. The average results of the evaluation using the cofussion matrix are accuracy of 0.72 .
Item Type: | Thesis (Skripsi) |
---|---|
Additional Information: | [No. Panggil : 1710511069] [Pembimbing : Iin Ernawati] [Penguji 1 : Ermatita] [Penguji 2 : Nurul Chamidah] |
Uncontrolled Keywords: | Sentiment Analysis, Classification, Online Learning, Twitter, Support Vector Machine (SVM) |
Subjects: | T Technology > TN Mining engineering. Metallurgy |
Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
Depositing User: | Alfiyah Nur Indraini |
Date Deposited: | 21 Dec 2021 07:53 |
Last Modified: | 21 Dec 2021 07:53 |
URI: | http://repository.upnvj.ac.id/id/eprint/11106 |
Actions (login required)
View Item |