Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal JUTIK : Jurnal Teknologi Informasi dan Komputer
Kunti Najma Jalia
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Engineering Social Sciences

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

Found 1 Documents
Search

 1 
IMPLEMENTASI LSTM UNTUK ANALISIS SENTIMEN PERSEPSI MASYARAKAT TERHADAP BANJIR SUMATERA 2025 DI YOUTUBE Kunti Najma Jalia; Adi Suwondo
Jurnal Teknologi Informasi dan Komputer Vol. 12 No. 1 (2026): JUTIK : Jurnal Teknologi Informasi dan Komputer, Edisi April 2026
Publisher : LPPM Universitas Dhyana Pura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36002/jutik.v12i1.5212

Abstract

Sumatra Flash Flood triggered extensive public discussion on social media regarding the causes of the disaster, particularly between natural factors and human factors. Understanding public perception is important for evaluating disaster literacy and mitigation communication strategies. This study analyzes public perceptions of the disaster’s causes using sentiment analysis based on the Long Short-Term Memory (LSTM) algorithm applied to YouTube comments. A total of 15,259 comments were collected using the YouTube Data API and processed through data cleaning and lexicon-based automatic labeling. After data selection, 11,043 comments were used for model training and testing. The experimental results show that the LSTM model achieved an accuracy of 96.29% and a ROC-AUC value of 0.99. Sentiment distribution analysis indicates that 57% of comments emphasize human factors, while 43% highlight natural factors or religious interpretations. These findings suggest an increasing public awareness of the human role in disaster risk and demonstrate the effectiveness of LSTM for Indonesian-language disaster sentiment analysis.
Co-Authors Adi Suwondo