TY  - JOUR
SP  - 303
N2  - PLN's mobile applications have become an important part of modern society, providing easy and fast services. However, the user experience of these apps often reflects dynamic changes in the technology environment and user needs. Therefore, sentiment analysis of user reviews becomes very important to find out what users feel and how best to improve the application. This thesis uses the Support Vector Machine (SVM) method to perform sentiment analysis of PLN Mobile app user reviews. SVM is an effective algorithm in text classification based on sentiment. Through this study, it is expected that the analysis results can be used for improvement and enhancement of the PLN Mobile application, thus providing a better user experience.
PB  - LPPM STIKOM Tunas Bangsa
EP  - 312
TI  - (KESATRIA - S4) - Faisal, Febriandirza, Hasan [2024-01-25]
UR  - http://www.pkm.tunasbangsa.ac.id/index.php/kesatria/article/view/339
IS  - 1
SN  - 2720-992X
A1  - Hasan, Firman Noor
Y1  - 2024/01/25/
VL  - 5
ID  - repository32133
JF  - KESATRIA: Jurnal Penerapan Sistem Informasi (Komputer & Manajemen)
AV  - public
ER  -