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All Journal Bulletin of Electrical Engineering and Informatics Scan : Jurnal Teknologi Informasi dan Komunikasi Jurnal Informatika dan Teknik Elektro Terapan Jurnal Sistem Informasi dan Bisnis Cerdas Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer JIEET (Journal of Information Engineering and Educational Technology) JUTIM (Jurnal Teknik Informatika Musirawas) bit-Tech UNTAG Law Review Jurnal Teknik Elektro dan Komputasi (ELKOM) JATI (Jurnal Mahasiswa Teknik Informatika) CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Jifosi Jurnal Pengabdian kepada Masyarakat Nusantara Nusantara Science and Technology Proceedings SOCIAL CLINICAL PHARMACY INDONESIA JOURNAL Journal of Social Research Jurnal Informatika Teknologi dan Sains (Jinteks) Journal of Governance and Administrative Reform Jurnal Teknik Informatika dan Teknologi Informasi Jurnal Informatika Polinema (JIP) Router : Jurnal Teknik Informatika dan Terapan Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi Router : Jurnal Teknik Informatika dan Terapan
Retno Mumpuni
Program Studi.Informatika, UPN Veteran Jawa Timur
Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Other

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Journal : bit-tech

 1 
Stres adalah masalah psikologis umum di kalangan Generasi Z, didorong oleh tekanan akademik, perbandingan sosial, dan paparan digital. Deteksi dini sangat penting untuk mencegah masalah kesehatan mental yang lebih parah seperti gangguan kecemasan, burnout Affandi, Ananda Asa Firstha; Rahmat, Basuki; Mumpuni, Retno
bit-Tech Vol. 8 No. 3 (2026): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3375

Abstract

Stress is a common psychological issue among Generation Z, driven by academic pressure, social comparison, and digital exposure. Early detection is essential to prevent more severe mental health problems such as anxiety disorders, burnout, or depression. This study aims to optimize a web-based stress detection system using the Recursive Feature Elimination (RFE) method combined with the Random Forest algorithm. A dataset consisting of 500 psychological assessment records and 12 symptom features (G01 to G12) from A3M Consultant Surabaya was used as the basis for analysis. RFE successfully reduced the number of features to six key indicators, such as G01 (anxiety), G02 (emotional instability), G04 (restlessness), G08 (withdrawal), G09 (confusion), and G12 (suicidal thoughts) while maintaining high model accuracy. The baseline Random Forest using 12 features achieved 0.91 accuracy, while the RFE-optimized model with 6 selected features maintained a comparable accuracy of 0.90. The resulting model achieved an accuracy of approximately 0.90 based on Stratified K-Fold Cross Validation, showing consistent performance across folds. The optimized model was then integrated into a web application called “The Z Space,” which combines data driven predictions from Random Forest with rule- based reasoning using Forward Chaining. This hybrid approach ensures both interpretability and accuracy in determining stress levels. The findings highlight that RFE effectively reduces computational complexity without decreasing model performance, making it suitable for real time web implementation in stress detection systems for Generation Z.
Sistem Absensi Desktop Menggunakan Face Recognition dan Pendekatan Adaptive Attendance Monitoring Afandy, Imam; Akbar, Fawwaz Ali; Mumpuni, Retno
bit-Tech Vol. 8 No. 3 (2026): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3487

Abstract

Manual attendance processes in higher education often face severe constraints regarding time inefficiency and vulnerability to data manipulation, specifically the prevalent issue of proxy attendance. Although Face Recognition technology has been widely adopted, most existing systems utilize a "once recognition" method, which fails to validate the student's presence throughout the entire lecture duration. This study aims to bridge this gap by developing an automatic desktop-based attendance system that integrates Face Recognition with a novel Adaptive Attendance Monitoring (AAM) approach. The proposed system utilizes a robust deep learning pipeline employing the Multi-Task Cascaded Convolutional Neural Network (MTCNN) for face detection and alignment, followed by FaceNet for generating 128-dimensional feature embeddings. To ensure real-time performance, the processing is accelerated by CUDA GPU technology on an NVIDIA RTX 4060 Ti. The system architecture follows a decoupled Client-Server model based on REST API, ensuring scalability and low-latency data transmission. The primary novelty of this research is the AAM algorithm, which continuously calculates the cumulative duration of a student's presence. A student is validated as "Present" only if they maintain visibility for at least 80% of the total session duration, effectively eliminating the "check-in and leave" loophole. Experimental results demonstrate that the system achieves a 100% recognition accuracy at an optimal distance of 1.0 meter under normal lighting conditions, with a processing latency consistently maintained under 100ms. These findings confirm that the proposed desktop-edge architecture significantly outperforms traditional mobile-based solutions in terms of stability, security, and continuous monitoring capabilities.
Web-Based Woven Fabric Recommendation System Integrated Fuzzy AHP and MOORA Based on User Preferences Bhakti, Mulyani Satya; Mumpuni, Retno; Nurlaili, Afina Lina
bit-Tech Vol. 8 No. 3 (2026): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3768

Abstract

This study proposes a web-based decision support system for woven fabric selection by integrating the Fuzzy Analytic Hierarchy Process (Fuzzy AHP) and Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA). The system addresses limitations in conventional selection processes that rely on subjective judgment and lack structured multicriteria evaluation. The proposed approach combines uncertainty-based weighting using Fuzzy AHP with objective ranking using MOORA, enabling a transparent and systematic decision-making process. Unlike previous hybrid MCDM-based recommender systems, this study integrates user preference modeling within a web-based framework and incorporates consistency validation and sensitivity analysis to ensure reliable results. The experimental results show that fabric type is the most influential criterion, with a weight of 0.33, and that alternative A4 consistently ranks as the best option, with an optimization value of 0.392. Sensitivity analysis shows that the ranking results remain stable across a 20% weight variation, and comparison with the SAW method confirms consistent rankings. In addition, User Acceptance Testing (UAT) involving 20 respondents achieves a score of 86.4%, indicating high usability and user satisfaction. However, the system is evaluated within a limited dataset and does not incorporate adaptive learning mechanisms. Therefore, future work is directed toward expanding the dataset and integrating machine learning-based approaches to enhance adaptability and scalability. Overall, the proposed system provides a structured, transparent, and empirically validated solution for multicriteria decision-making.
Design of Web-Based Decision Support System Using AHP and bcrypt Security Subagio, Moh. Mario; Mumpuni, Retno; Nurlaili, Afina Lina
bit-Tech Vol. 8 No. 3 (2026): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3769

Abstract

This study presents the development of a web-based decision-support system to prioritize village administrative services using a structured, data-driven approach. This research addresses a gap in existing systems, which generally lack integration of systematic decision-making methods and robust security mechanisms, leading to inefficiency, low transparency, and subjective decision-making in village administrative processes. To overcome these limitations, the system integrates the Analytical Hierarchy Process (AHP) to evaluate multiple criteria, including submission time, document completeness, urgency level, service type, and request frequency, thereby enabling qualitative assessments to be transformed into measurable, comparable priority values. In addition, the bcrypt algorithm enhances system security by protecting user authentication data through password hashing, thereby mitigating risks such as unauthorized access, brute-force attacks, and rainbow-table attacks. The system is developed as a web-based application to ensure accessibility, scalability, and centralized data management. Evaluation results indicate that the system produces consistent and reliable priority rankings, as evidenced by a Consistency Ratio (CR) within the acceptable threshold, and demonstrates improved decision accuracy and operational efficiency compared to conventional manual approaches. Document completeness is identified as the most influential criterion in determining service priority. Furthermore, the proposed system offers broader applicability beyond village administration, particularly in other public service domains requiring transparent, efficient, and secure decision-making processes. Overall, this study contributes by integrating AHP and bcrypt within a unified system to enhance both decision quality and data security in digital administrative services.
Co-Authors Ach.Diki Prasetyo, Ach.Diki Prasetyo Aditiawan, Firza P. Afandi, Rizal Afandy, Imam Affandi, Ananda Asa Firstha Affandi, Masfi Ulil Afina Lina Nurlaili Ahmad Hilman Dani Akbar, Fawwaz Ali Alatas, Amirah Alvian Dwiangga Wijaya Alvian Dwianngga Wijaya Amirah Tsany Alatas Andreas Nugroho Sihananto Anggriawan, Teddy Prima Ani Dijah Rahajoe Arfiqi, Fawwaz Aulia N, Rayhan Basuki Rahmat Basuki Rahmat Masdi Siduppa Bhakti, Mulyani Satya Budi Nugroho Burhanuddin Muhammad Zhirof Damayanti, Alfina Davila Erdianita Dicky Satria Mahendra Endang Sholihatin Eva Yulia Puspaningrum Fadillah, Mochamad Nor Faisal Muttaqin Farhana, Hafi Ihza Faruq Asshegaff, M. Alvin Fetty Tri Anggraeny Fian Pahothon Sukawidayanta, Octavianus Firza Prima Aditiawan Hamzah Dimas Syah Reza Hendra Suryawan, Danil Henni Endah Wahanani Herdi Rofaldi KARTINI Lina Nurlaili, Afina Lintas, Ilham Lintas Perdana Made Hanindia Prami Swari Mahanani, Anajeng Esri Edhi Mandyartha, Eka Prakarsa Mochamad Nor Fadillah Nugroho Gultom, Wahyu Nurlaili, Afina Lina Pande Putu Sunaryang Yogam Prasanta Parlika, Rizky Pramnesti, Adisty Regina Ramadhan, Dimas Dharu Rizki, Agung M. Ronggo Alit Roziana Febrianita Sanjaya, Alvian Dwi Satria, Ramadhan Dani Septian Anggraini, Safira Septyono, Muhammad Bagas Setiawan, Rienaldi Subagio, Moh. Mario Sugiarto Syahrul Munir Syahrul Munir Tarigan, Puji L. Thooriqoh, Hazna At Vita Via, Yisti Wariyanti Nugroho Putri Winata, Chycik Ayu yisti vita via Yisti Vita Via