I Gusti Naufhal Daffa Adnyana, . (2021) ANALISIS SENTIMEN TENTANG UU CIPTA KERJA MENGGUNAKAN ALGORITMA NAÏVE BAYES. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
Text
ABSTRAK.pdf Download (13kB) |
|
Text
AWAL.pdf Download (920kB) |
|
Text
BAB 1.pdf Download (253kB) |
|
Text
BAB 2.pdf Restricted to Repository UPNVJ Only Download (646kB) |
|
Text
BAB 3.pdf Restricted to Repository UPNVJ Only Download (617kB) |
|
Text
BAB 4.pdf Restricted to Repository UPNVJ Only Download (1MB) |
|
Text
BAB 5.pdf Download (236kB) |
|
Text
DAFTAR PUSTAKA.pdf Download (350kB) |
|
Text
RIWAYAT HIDUP.pdf Restricted to Repository UPNVJ Only Download (23kB) |
|
Text
LAMPIRAN.pdf Restricted to Repository UPNVJ Only Download (957kB) |
|
Text
ARTIKEL KI.pdf Restricted to Repository UPNVJ Only Download (859kB) |
Abstract
Twitter is a platform that allows people to express their wishes, opinions and critiques directly. The ratification and promulgation of the Omnibus Law has generated many diverse opinions in the community, especially Twitter users. The purpose of this study is to understand the opinions of Twitter users on the Omnibus Law through the hashtag #UUCIPTAKERJA. In this study, public opinion is classified as positive and negative, then the Naive Bayes algorithm is used to classify tweets. The data is taken starting from October 5 - November 30, 2020 using the API provided by Twitter. The test results obtained using test data have an accuracy value of 80.53%, a recall value of 84.78%, and a specificity value of 73.79%.
Item Type: | Thesis (Skripsi) |
---|---|
Additional Information: | [No. Panggil : 1710511082] [Pembimbing 1 : Ermatita] [Pembimbing 2 : Sarika] [Penguji 1 : Yuni Widiastiwi] Penguji 2 : Nurul Chamidah] |
Uncontrolled Keywords: | Twitter, Omnibus Law, Classification, Naïve Bayes |
Subjects: | T Technology > T Technology (General) |
Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
Depositing User: | I Gusti Naufhal Daffa Adnyana |
Date Deposited: | 21 Dec 2021 07:26 |
Last Modified: | 21 Dec 2021 07:26 |
URI: | http://repository.upnvj.ac.id/id/eprint/11208 |
Actions (login required)
View Item |