Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Building of Informatics, Technology and Science
Tri Ayu Syifa'ur Rohmah
Telkom University, Bandung
Computer Science & IT

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Personality Detection on Twitter Social Media Using IndoBERT Method Tri Ayu Syifa'ur Rohmah; Warih Maharani
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.1895

Abstract

Personality is the fundamental characteristic of human beings that makes humans unique. Because of these differences in human characteristics, personality becomes a benchmark for consideration in various recruitment processes. One way to predict personality is to apply an interview system or fill out questionnaires which often experience problems due to ineffectiveness in terms of time and cost. Results become inaccurate if prospective employees do not know themselves well. The big five personality method, divided into openness, conscientiousness, extraversion, agreeableness, and neuroticism, is widely used to predict personality. This study uses a deep learning method, IndoBERT, to detect personality based on five dimensions according to the big five personalities whose data is taken from Twitter tweets with crawling data. From the results of these studies, it is known that personality research using the IndoBERT method without a stemming process has a higher accuracy rate of 0.46.
Co-Authors Warih Maharani