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All Journal Informatika Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Ayun, Aisyah Qurrata
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Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Library & Information Science Other

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Efektivitas dan Kelemahan Autentikasi Berbasis Web Menggunakan One-Time Password (OTP) dalam Mencegah Akses Tidak Sah Maulana, Fajar; Hendra, Yomei; Sakinah, Putri; Eirlangga, Yofhanda Septi; Ayun, Aisyah Qurrata
Jurnal Informatika Vol 12, No 3: INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v12i3.7482

Abstract

Authentication based on one-Time Password (OTP) is one method that is widely used in securing access to web systems. This study aims to analyze in depth the effectiveness and weaknesses of the OTP authentication system in preventing unauthorized access. Through a qualitative approach based on literature studies, as well as comparisons between other authentication methods, it was found that OTP is able to increase a significant additional layer of security, especially when combined with other authentication methods such as passwords or biometrics. However, this system still has various weaknesses, such as the risk of phishing attacks, man-in-the-middle (MITM) attacks, and vulnerabilities to SIM swapping attacks, especially in the implementation of OTP via SMS. Dependence on user devices and communication networks is also a limiting factor in the effectiveness of OTP. This study provides recommendations for the implementation of strengthening measures such as Multi-Factor Authentication (MFA), the use of authenticator applications, and the implementation of end-to-end encryption to reduce security risks. The results of this study are expected to be a reference for system developers and organizations in choosing and implementing authentication methods that are more secure and in accordance with current cybersecurity needs.
Sentiment Analysis of Gojek App Reviews on Google Play Store with Natural Language Processing Using Naive Bayes' Algorithm Rahman, Zumardi; Sakinah, Putri; Hendra, Yomei; Satria, Budy; Maulana, Fajar; Ayun, Aisyah Qurrata
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 6 No. 03 (2024): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v6i03.1189

Abstract

In the digital era, sentiment analysis is an important tool to understand user perceptions of applications, including the Gojek application. This study aims to analyze the sentiment of Gojek application user reviews on the Google Play Store using the Naive Bayes algorithm. The research process involved collecting 5,000 reviews, preprocessing the text, weighting with TF-IDF, and applying the Naive Bayes algorithm to classify sentiment into negative, neutral, and positive. The evaluation results show that the model has the best accuracy of 76% after applying the data balancing technique. The model's performance for negative sentiment is very good with a precision of 91% and an F1 score of 87%. Positive sentiment shows quite good performance with a precision of 76% and an F1 score of 65%. However, neutral sentiment has low precision (23%) although recalls increased to 51%. Sampling techniques such as SMOTE have succeeded in improving the model's ability to recognize underrepresented classes. With an overall evaluation of weighted average precision of 82% and an F1 score of 78%, this model is considered quite reliable in analyzing the sentiment of Gojek app reviews. This research provides insights for application developers in improving service quality based on user perception..
Co-Authors Hendra, Yomei Maulana, Fajar Rahman, Zumardi SAKINAH, PUTRI Yofhanda Septi Eirlangga