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All Journal Jurnal Infra Agora Jurnal Ekonomi & Studi Pembangunan Jurnal Psikologi Ulayat: Indonesian Journal of Indigenous Psychology Computatio : Journal of Computer Science and Information Systems JRSI (Jurnal Rekayasa Sistem dan Industri) JOURNAL OF APPLIED INFORMATICS AND COMPUTING TESLA: Jurnal Teknik Elektro Jurnal Psikologi Ulayat: Indonesian Journal of Indigenous Psychology SULTANIST: Jurnal Manajemen dan Keuangan Technologia: Jurnal Ilmiah Journal of Applied Information, Communication and Technology Journal of Applied Data Sciences International Journal of Social Service and Research Cessie : Jurnal Ilmiah Hukum Jurnal Ilmiah MEA (Manajemen, Ekonomi, dan Akuntansi) Jurnal Manajemen Sistem Informasi Nexus Synergy: A Business Perspective The International Journal of Medical Science and Health Research Jurnal Pengabdian Masyarakat Trimedika
christian christian
Program Studi Teknik Informatika
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Nursing Public Health Social Sciences Veterinary Other

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Journal : JOURNAL OF APPLIED INFORMATICS AND COMPUTING

 1 
Enhancing Web Security and Performance with Hybrid Stateless Authentication Mario, Benedictus; Wiradinata, Trianggoro; Christian, Christian
Journal of Applied Informatics and Computing Vol. 9 No. 3 (2025): June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i3.9251

Abstract

Ensuring operational integrity across industries and protecting sensitive data require strong authentication systems. This paper presents a novel hybrid stateless authentication method that integrates binary payloads, token specifications, and database solutions. By employing a distinctive expiration policy, our proposed approach overcomes limitations inherent in traditional token revocation strategies while achieving token verification speeds that are up to 86 times faster than conventional statefull session-based methods. Overall, through uniformed benchmarking experiments and a comprehensive review of the literature substantiate the performance and security advantages of our method. Ultimately, this hybrid technique offers a more scalable and secure framework for authentication management, enabling efficient and flexible deployment in high-demand distributed environments.
Behavioural Predictors of Forward Head Posture Risk: A Correlation, Machine Learning, and Clustering Analysis Putri Lo, Angel Aprilia; Christian, Christian
Journal of Applied Informatics and Computing Vol. 10 No. 1 (2026): February 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i1.12089

Abstract

Forward Head Posture (FHP) has become increasingly common among university students due to prolonged digital device use and inadequate ergonomic behaviour. This study aims to identify the behavioural factors that most strongly predict neck tension, which is used as an indicator of FHP risk, among laptop users at Universitas Ciputra. A total of 141 survey responses were collected, capturing digital lifestyle patterns that include screen exposure, posture habits, ergonomic awareness, physical activity, and screen-related symptoms. The analysis followed a complete methodological sequence that involved data preprocessing, correlation testing, supervised machine-learning modelling, and K-Means clustering. The results show that headache after screen use, frequency of head-down posture, ergonomic knowledge, and weekly exercise emerged as the most influential behavioural predictors of neck tension, with head-down posture demonstrating the strongest association (r = 0.437). Correlation testing supported three of the four hypotheses, while the Random Forest model achieved the highest predictive performance (71.01% cross-validated accuracy). The clustering analysis revealed two distinct behavioural subgroups with different ergonomic risk profiles. These findings highlight specific behavioural targets that can support ergonomic-awareness efforts and help reduce the likelihood of FHP development in academic environments.
Co-Authors Adi Suryaputra Paramita Al-aytami, Abdul Musyfiq Amirudin, Dede Anthony Anthony Ariesa, Yeni Christian, Natalis Clara Moningka Darmasaputra, Albert Diani Nazma Dyah Erny Herwindiati Edwin Kurniawan Elizabeth Nathania Witanto Endah Setyaningsih Ernalem Jawak, Pelita Felim, Nicholas Fitriani Fitriani Gonardi, Jesslyn Gonardi, Jesslyn Hang Suharto Hendryli, Janson Hilyah Magdalena I Eng, Kho Indra Maryati Ipung, Heru Purnomo Johanna, Felita Johanna, Felita Laksmi, Antin Tri Lira Panduwaty Mahardieni, Karlina Mario, Benedictus Nurseha, Samsudin Onn, Choo Wou Pina, Pina Purnomo, Kevin Purnomo, Kevin Putri Lo, Angel Aprilia Rusdianto Roestam Rustam, Rinaldi Sembiring, Rinawati Septryanti, Ade Silvana, Versia Silvia Rostianingsih Sonya Airini Batubara, Sonya Airini Surya, Vincent Alain Tileubaevna, Auezova Raya Trianggoro Wiradinata Wijaya, Evelyn William Onnyxiforus Purnomo, William Onnyxiforus Wiratama, Stefani Gisella Wiratama, Stefani Gisella Yosua Setyawan Soekamto