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Design Of Web-Based Online Booking Application For Motor Vehicle Repair Using Codeigniter Framework: Study At One Of The Motorcycle Workshop In Bandung Tasya Nurul Anisa; Asep Ririh Riswaya; Oktavia Oktavia; En Tay
Informatics Management, Engineering and Information System Journal Vol. 3 No. 1 (2025): Informatics Management, Engineering and Information System Journal
Publisher : LPPM STMIK Mardira Indonesia

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Abstract

This study presents the development and testing of an IoT-based temperature and humidity management system designed for mushroom cultivation. The system effectively utilizes a DHT sensor and a scheduling mechanism to monitor and control environmental conditions. Key findings reveal that the IoT-based control system allows mushroom farmers to access real-time data through a user-friendly web interface and control unit, facilitating immediate adjustments to optimize growth conditions. Testing confirmed the system's capability to maintain essential temperature and humidity levels: 22–28°C and 80–90% during mycelium development and 16–25°C and 90–95% during the fruiting body stage. These controlled conditions significantly enhance mushroom growth and productivity compared to traditional cultivation methods. The implementation of this IoT-based system not only improves the quality and yield of mushroom production but also increases operational efficiency for farmers. By integrating modern technology into agricultural practices, this study demonstrates the potential of IoT to transform conventional farming approaches into more effective and sustainable operations.
Forensic Evaluation of the Effectiveness of Private Browsing Modes in Google Chrome and Mozilla Firefox Using the National Institute of Standards and Technology Framework Integrated with Artificial Intelligence Syukri, Muhammad; Riswaya, Asep Ririh; Budiman, Dheni Apriantsani
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 2 (2026): JUTIF Volume 7, Number 2, April 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.2.5577

Abstract

As cyber threats and the misuse of personal data continue to increase, private browsing modes in web browsers such as Google Chrome and Mozilla Firefox are often perceived as solutions to enhance user privacy. However, these modes still leave traces of sensitive data in volatile memory (RAM), even though artifacts stored on disk-based storage are removed. This study evaluates the effectiveness of private browsing modes using the National Institute of Standards and Technology (NIST) framework integrated with Artificial Intelligence (AI) for forensic analysis. Simulation scenarios were conducted to assess the ability of private browsing modes to prevent data retention. The results indicate that although private browsing modes successfully eliminate disk-based traces, sensitive data such as account credentials can still be extracted from RAM. The integration of AI accelerates the detection of these artifacts. This research contributes to the field of digital forensics by providing a systematic framework for evaluating browser privacy mechanisms and offering insights for the development of real-time browser security tools.