Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal Economic Reviews Journal Jasmine : Journal of Intelligent Systems and Machine Learning
Mutia Ulfa
Universitas Sugeng Hartono
Economics, Econometrics & Finance Industrial & Manufacturing Engineering Social Sciences

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Deep Learning Model for Identification of Indonesian National Figure Entities on Social Media Using LSTM Architecture Very Setiawan; Dwi Utari Iswavigra; Mutia Ulfa
JASMINE: Journal of Intelligent Systems and Machine Learning Vol. 1 No. 1 (2026)
Publisher : Universitas Telkom

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/jasmine.v1i1.10057

Abstract

In the era of rapid digital communication, social media has become a dominant medium for information exchange and public discourse, particularly in Indonesia. Despite this growth, automatic identification of national figures within social media texts remains a significant challenge due to the informal nature of language, frequent abbreviations, and inconsistent spelling patterns. Addressing this gap, this study aims to develop a Deep Learning model based on Long Short-Term Memory (LSTM) networks to identify Indonesian national figures from social media texts. The research utilizes 1,109 tweets collected from X (formerly Twitter) through the X API, encompassing names of well-known figures from politics, sports, entertainment, and social activism. The research process includes dataset crawling, preprocessing, labeling using the spaCy library, dividing training and test data, and training an LSTM model. The evaluation results show that the proposed model achieves a high level of performance, achieving 97.8% accuracy, 96% precision, 93% recall, and an F1-score of 92% on the validation data, demonstrating the LSTM model's ability to make accurate and reliable predictions. Word cloud analysis shows that the model is able to consistently recognize person entities such as "Prabowo", "Sri Mulyani", and "Agnez Mo". However, the model still experiences limitations in detecting unfamiliar or rarely appearing entities. Overall, this study shows that the combination of spaCy and LSTM is effective for NER tasks on Indonesian social media texts and has the potential for further development with increased data variety and improvements to the labeling process.
Literasi Keuangan Digital sebagai Determinan Perilaku Menabung Generasi Z di Indonesia Agatha Pricillia Sekar Tamtomo; Mutia Ulfa; Graceilla Kristia Seraphim Budiono; Ahmad Aufar Ribhi; Muhammad Anwar Fauzi
Economic Reviews Journal Vol. 5 No. 1 (2026): Economic Reviews Journal
Publisher : Masyarakat Ekonomi Syariah Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56709/mrj.v5i1.1076

Abstract

This study aims to examine the influence of digital financial literacy on the saving behavior of Generation Z in Indonesia based on findings from previous studies. A qualitative approach was employed through a literature review of eleven relevant scientific articles discussing digital financial literacy and saving behavior, particularly among Generation Z and university students. The results indicate that the majority of studies report a positive and significant relationship between digital financial literacy and saving behavior. This suggests that individuals with higher levels of digital financial literacy tend to have better financial management skills and demonstrate stronger saving habits. However, several studies present contrasting findings. Some research revealed that financial literacy does not have a significant effect on students’ saving behavior or saving intentions. These findings imply that financial knowledge alone may not be sufficient to encourage consistent saving practices, as saving behavior may also be influenced by internal factors such as self-discipline and personal financial control. Based on the review of the selected articles, it can be concluded that digital financial literacy generally has a positive and significant influence on the saving behavior of Generation Z in Indonesia, although its impact may vary depending on individual characteristics.
Co-Authors Agatha Pricillia Sekar Tamtomo Ahmad Aufar Ribhi Dwi Utari Iswavigra Graceilla Kristia Seraphim Budiono Muhammad Anwar Fauzi Very Setiawan