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All Journal JEECS (Journal of Electrical Engineering and Computer Sciences) Jasmine : Journal of Intelligent Systems and Machine Learning
Elizabeth Piscelia Kusuma
Universitas Pignatelli Triputra
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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SmartNotes Encrypted with Hybrid Cryptography Combining Rivest Cipher 4 and XChaCha20 Elizabeth Piscelia Kusuma; Aqeela Nashwa Naysilla; Bagas Dwi Yulianto
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 10 No. 2 (2025): December
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v10i2.5

Abstract

Digital note-taking applications serve as essential tools for personal information management, presenting opportunities for enhanced security mechanisms to protect sensitive data. Most current solutions depend on server-side processing, creating potential vulnerabilities and privacy concerns. However, a robust solution that fully executes hybrid encryption on the client-side to seamlessly protect both text and image data within a single application remains unexplored. This study introduces SmartNotes, a web-based application safeguarding text and image notes through an innovative hybrid encryption system synergistically combining RC4 and XChaCha20 algorithms. A key contribution is the full client-side execution of encryption–decryption processes, eliminating server dependencies and significantly reinforcing data confidentiality. The hybrid design strategically utilizes RC4 for rapid data processing and XChaCha20 for robust cryptographic protection, creating an optimal balance between performance and security.  System performance was rigorously evaluated using seven private datasets under diverse key conditions. Testing methodology included comprehensive assessment of processing speed, data integrity verification, and resistance against unauthorized access attempts. Results demonstrated flawless data restoration across all test cases, validating robustness and reliability. Encryption averaged 1.5 seconds, while decryption required 20.20 seconds metrics well-suited for practical web environments. These findings affirm SmartNotes delivers a secure, autonomous, user-centric solution for digital note management, advancing applied cryptography through a novel client-side hybrid encryption paradigm. This approach successfully balances strong security with practical performance, making it suitable for securing data in everyday web applications.
Detection and Classification of Cognitive Distortions in Mental Health Texts Using a Hybrid Natural Language Processing Approach Elizabeth Piscelia Kusuma; Aan Shandy Rahesa; Christin Yulianti; Samuel Ardhian Trisunu
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.v1i1.10150

Abstract

This study develops a hybrid natural language processing system to detect cognitive distortions in Indonesian text, aiming to support early mental health awareness. The proposed model integrates rule-based keyword matching with a Random Forest classifier, leveraging TF-IDF feature extraction from the preprocessed Indonesian Mental Health Conversation dataset. Evaluation against manually labeled data across eight distortion categories shows the hybrid approach outperforms standalone methods, achieving a classification accuracy of 77.5% and an exact match rate of 76.67%. The system demonstrated robust performance and fairness, maintaining a balanced label distribution across categories and achieving a validation accuracy of 94% on the full dataset. To validate real world applicability, the model was integrated into a reflective chatbot that successfully identifies distorted thinking patterns in user input and retrieves contextually relevant responses. These findings confirm that combining linguistic theory with data driven modeling creates an effective, interpretable, and scalable tool for cognitive distortion detection in informal Indonesian psychological text.
Co-Authors Aan Shandy Rahesa Aqeela Nashwa Naysilla Bagas Dwi Yulianto Christin Yulianti Samuel Ardhian Trisunu