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All Journal INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Advance Sustainable Science, Engineering and Technology (ASSET)
Mohamed Naeem Antharathara Abdulnazar
ISMA University
Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering

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Integrating Cryptographic Security Features in Information System Barcodes for Self-Service Systems Sucipto; Aidina Ristyawan; Dwi Harini; Wahid Ibnu Zaman; Muhammad Najibulloh  Muzaki; Mohamed Naeem Antharathara Abdulnazar
Advance Sustainable Science Engineering and Technology Vol. 6 No. 4 (2024): August-October
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v6i4.850

Abstract

Integrating services in an information system is necessary to provide services that can optimize an information system. One of the systems in PKKMB activities that will be combined with information security features is the attendance system. This research uses the Liner Sequential Model (LSM) method to integrate the QR Code attendance system with security features. This research aims to integrate QR Codes by optimizing increased security by combining the Advanced Encryption Standard (AES) algorithm with base64 with a dynamic data model to complicate the QR Code manipulation process. Contribution This study makes optimization of the AES encryption model to improve data security on QR Code. Algorithm testing results include using a Character Error Rate (CER) of 0%, Avalanche Effect (AE) testing with a value of 53.05%, and response time (RT) testing of 10.26ms
Enhancing Multi-Class Classification of Non-Functional Requirements Using a BERT-DBN Hybrid Model Badzliana Aqmar Suris; Aris Thobirin; Sugiyarto Surono; Mohamed Naeem Antharathara Abdulnazar
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 9 No 2 (2025): August 2025
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v9i2.24637

Abstract

Background: Software requirements classification is essential to group Non-Functional Requirements (NFR) into several aspects, such as security, usability, performance, and operability. The main challenges in NFR classification are data limitations, text complexity, and high generalization needs. Objective: This research seeks to create a classification model using a hybrid of BERT and DBN, optimize hyperparameters, and improve data representation. Methods: A BERT and DBN-based approach is used, where DBN enhances BERT's ability to extract hierarchical features. Bayesian Optimization determines the optimal hyperparameters and data augmentation is applied to enrich the dataset variation. The model is tested on the PROMISE dataset consisting of 625 data. Results: The BERT-DBN model achieves 95% accuracy on the baseline configuration and 94% on the extensive configuration, better than the previous model, BERT-CNN. The model shows stability without any indication of overfitting. Conclusion: The combination of data augmentation, hyperparameter optimization, and DBN's ability to capture hierarchical patterns improves the accuracy of NFR classification, making it more effective than existing methods, and is expected to enhance text-based classification for software requirements.
Integrating Cryptographic Security Features in Information System Barcodes for Self-Service Systems Sucipto; Aidina Ristyawan; Dwi Harini; Wahid Ibnu Zaman; Muhammad Najibulloh  Muzaki; Mohamed Naeem Antharathara Abdulnazar
Advance Sustainable Science Engineering and Technology Vol. 6 No. 4 (2024): August-October
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v6i4.850

Abstract

Integrating services in an information system is necessary to provide services that can optimize an information system. One of the systems in PKKMB activities that will be combined with information security features is the attendance system. This research uses the Liner Sequential Model (LSM) method to integrate the QR Code attendance system with security features. This research aims to integrate QR Codes by optimizing increased security by combining the Advanced Encryption Standard (AES) algorithm with base64 with a dynamic data model to complicate the QR Code manipulation process. Contribution This study makes optimization of the AES encryption model to improve data security on QR Code. Algorithm testing results include using a Character Error Rate (CER) of 0%, Avalanche Effect (AE) testing with a value of 53.05%, and response time (RT) testing of 10.26ms
Co-Authors Aidina Ristyawan Aris Thobirin Badzliana Aqmar Suris Dwi Harini Muhammad Najibulloh Muzaki Sucipto Sucipto Sugiyarto Surono Wahid Ibnu Zaman