JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika)
Vol 8, No 1 (2023)

DEPRESSION DETECTION ON SOCIAL MEDIA TWITTER USING XLNET METHOD

Fika Apriliani (Telkom University)
Warih Maharani (Telkom University)



Article Info

Publish Date
25 Feb 2023

Abstract

Depression is a serious mental illness. Depression is usually characterized by feelings of sadness, hopelessness, anxiety, restlessness, and even loss of life. However, not everyone who experiences depression can get professional treatment. If depression is left unchecked, it can worsen the mental health conditions experienced by a person. Social media, one of which is the increasingly popular twitter can be utilized to help deal with the problem of undetected mental illness. Based on tweets made by a person twitter social media can be one of the sources to detect depression using the XLNet method. XLNet is one of the NLP (Natural Language Processing) techniques based on machine learning models on text. Based on several tests that have been carried out during the research such as testing various tuning hyper-parameters with different values on the XLNet model, it achieves a good performance value with an average accuracy value of 93.33%.

Copyrights © 2023






Journal Info

Abbrev

Publisher

Subject

Computer Science & IT Education

Description

JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) e-ISSN: 2540 - 8984 was made to accommodate the results of scientific work in the form of research or papers are made in the form of journals, particularly the field of Information Technology. JIPI is a journal that is managed by the ...