This article presents the design, implementation, and evaluation of a Student Absence Management System (SAMS) tailored for university environments. The system integrates web frontends, Google Apps Script backends, Google Sheets storage, and Google Drive for evidence handling, delivering end-to-end workflows for leave application, multi-level approvals, notification, and record keeping. Our key novelty lies in architecting a serverless, low-ops absence workflow atop managed Google services, demonstrating role-based access control (RBAC) patterns with deterministic state transitions, and establishing resilience through separation of critical operations from non-critical side effects. We discuss the motivating context, survey related work, describe the architecture and algorithms, report observed outcomes, and outline future directions. Pilot deployment results show a 75% reduction in processing time (from 2--3 days to <8 hours), a 95% reduction in evidence availability issues, and maintained auditability through timestamped, deterministic approval logs with <2\% user-facing failures.

Keywords: Serverless, Digitization, Transformation, System, Software Engineering, University, Workflows, Google, Playbook, System Design.

[1] Ahmad, M., et al. (2025). Learning three-dimensional face recognition from sparse views for robust identity verification. SSRN. https://ssrn.com/abstract=5428214.

[2] Akram, F., et al. (2024). Integrating artificial bee colony algorithms for deep learning model optimization: A comprehensive review. In Solving with Bees: Transformative Applications of Artificial Bee Colony Algorithm, Pages 73–102. https://doi.org/10.1007/978-981-97-7344-2_5.

[3] Al Omari, O.M.A., Khan, N.A., & Mahafdah, R. (2017). Ranking and reputation based resource allocation in P2P system. Mediterranean Journal of Basic and Applied Sciences, 1(1): 293–301.

[4] Alanezi, R., Alanezi, M.A., & Khan, N.A. (2018). Development of web based e-cooperative training system. In 2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE). 

[5] Alangari, S., et al. (2022). Developing a blockchain-based digitally secured model for the educational sector in Saudi Arabia toward digital transformation. PeerJ Computer Science, 8: e1120. 

[6] Alangari, S., & Khan, N.A. (2021). Artificially intelligent warehouse management system. Asian Journal of Basic Science & Research, 3(3): 16–24. https://doi.org/10.38177/ajbsr.2021.3302.

[7] Khan, N., et al. (2025). Network intrusion management of web form spamming using blockchain. Irish Interdisciplinary Journal of Science & Research, 9(3). https://doi.org/10.46759.

[8] Khan, N.A. (2018). Cloud applications development and deployment: The future of cost-effective programming and a step ahead. Middle East Journal of Applied Science & Technology, 1(1): 30–36.

[9] Khan, N.A. (2019). Security management protocols in cloud computation. Middle East Journal of Applied Science & Technology, 2(1): 16–23.

[10] Khan, N.A., et al. (2019). Intrusion management to avoid web-form spamming in cloud based architectures. In 2019 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE). https://doi.org/ 10.1109/iccike47802.2019.9004302.

[11] Khan, N.A., et al. (2019). Prevention of web-form spamming for cloud based applications: A proposed model. In Amity International Conference on Artificial Intelligence (AICAI).

[12] Khan, N.A. (2019). Wireless requirements and benefits in the academics domain. Middle East Journal of Applied Science & Technology, 2(3): 45–49.

[13] Khan, N.A. (2019). Basics of ethical hacking and computer security.

[14] Aljomaee, W.Y., Alshahrani, S.M., & Khan, N.A. (2025). NAMAQ-Arabic handwriting recognition using deep learning, AI, and ML with sentiment analysis. In 2025 4th International Conference on Computing and Information Technology (ICCIT). https://doi.org/10.1109/iccit63348.2025.10989445.

[15] Khan, N.A., & Ghamdi, A. (2015). Cyber forensics and proposed techniques to overcome cyber threats for cyber security. International Journal of Engineering and Management Research, 5(5): 187–191.

[16] Alshalaan, M., & Khan, N.A. (2025). Complexities and challenges for securing digital assets and infrastructure in academia: A review on digital asset security. In Complexities and Challenges for Securing Digital Assets and Infrastructure, Pages 225–244. https://doi.org/10.4018/979-8-3373-1370-2.ch011.

[17] Almalki, J., et al. (2022). Enabling blockchain with IoMT devices for healthcare. Information, 13(10): 448. https://doi.org/10.3390/info13100448.

[18] Almalki, J., Alshahrani, S.M., & Khan, N.A. (2024). A comprehensive secure system enabling healthcare 5.0 using federated learning, intrusion detection and blockchain. PeerJ Computer Science, 10: e1778. 

[19] Khan, N.A. (2019). Measuring academics intentions to use a project management system (PMS): A case study of the College of Computing and Information Technology, Shaqra University. Trends in Future Informatics and Emerging Technologies, Pages 58–69.

[20] Khan, N.A. (2025). Statistical probability prediction model for e-learning and realtime proctoring using IoT devices. Journal of King Saud University – Science, 37: 7002025.

[21] Alshahrani, S.M., et al. (2023). Systematic survey on big data analytics and artificial intelligence for COVID-19 containment. Computer Systems Science & Engineering, 47(2). https://doi.org/10.32604/csse.2023. 039648.

[22] Alshahrani, S.M., & Khan, N.A. (2023). COVID-19 advising application development for Apple devices (iOS). PeerJ Computer Science, 9: e1274. https://doi.org/10.7717/peerj-cs.1274.

[23] Alshahrani, S.M., et al. (2022). URL phishing detection using particle swarm optimization and data mining. Computers, Materials & Continua, 73(3). https://doi.org/10.32604/cmc.2022.030982.

[24] Alshalaan, M., & Khan, N.A. (2025). Blockchain-enabled federated learning framework for secure and collaborative drug discovery: Integrating AI, molecular docking, and distributed ledger technology. 

[25] Alsulami, M.H., Alotaibi, S., & Khan, N. (2021). Smart university model for Saudi Arabian universities. Design Engineering, Pages 162–181.

[26] Alsulami, M.H., et al. (2021). Zigbee technology to provide elderly people with well-being at home. International Journal of Sensors Wireless Communications and Control, 11(9): 921–927. 

[27] Hassan, M.A.A., Khan, N.A., & Nasim, M.A. (2017). Managing data replication in mobile ad-hoc network databases using content based energy optimization. Mediterranean Journal of Basic and Applied Sciences, 1(1): 142–154.

[28] Khan, N.A. (2024). Development of intelligent pick and drop service manager for small cities. Asian Journal of Basic Science & Research, 6(3): 20–27. https://doi.org/10.38177/ajbsr.2024.6303.

[29] Khan, N.A. (2024). Development of intelligent help system for small cities. Asian Journal of Applied Science and Technology, 8(3): 112–119. https://doi.org/10.38177/ajast.2024.8311.

[30] Khan, N.A. (2025). Development of intelligent student information system. Arabian Journal of Basic Science and Research, 7(1). https://doi.org/10.38177/ajbsr.2025.7101.

[31] Khan, N.A., et al. (2021). Development of Mubadarah system – An intelligent system for proposals at a university. In 2021 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE). https://doi.org/10.1109/iccike51210.2021.9410773.

[32] Khan, N.A., et al. (2021). Development of Medidrone: A drone based emergency service system for Saudi Arabian healthcare. In 2021 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE). https://doi.org/10.1109/iccike51210.2021.9410685.

[33] Khan, N.A., Rajeyyagari, S., & Khan, A.R. (2025). Development of intelligent library services for university students. Mediterranean Journal of Basic and Applied Sciences, 9(1): 142–147. 

[34] Khan, N.A., Siddiqi, A.M.U., & Ahmad, M. (2021). Development of intelligent alumni management system for universities. Asian Journal of Basic Science & Research, 3(2): 51–60. https://doi.org/10.38177/ajbsr.2021. 3206.

[35] Khan, N.A., & Ahamad, D. (2025). Living smart: AI-based urban assistance systems for sustainable wellbeing in small cities. https://doi.org/10.46431/mejast.2025.8210.

[36] Khan, N.A., et al. (2025). Transformative impact of artificial intelligence on higher education: A comprehensive analysis of pedagogical innovation, institutional transformation, and future learning ecosystems. Asian Journal of Applied Science and Technology, 9(4): 57–76.

[37] Khan, N.A., et al. (2024). An IoMT enabled iterative artificial bee colony approach using federated learning for detection of heart disease. In Solving with Bees: Transformative Applications of Artificial Bee Colony Algorithm, Pages 103–116. https://doi.org/10.1007/978-981-97-7344-2_6.

[38] Khan, N.A., et al. (2021). An empirical analysis on users’ acceptance and usage of BYOD-technology for Saudi universities: A case study of Shaqra University. In 2021 International Conference on Technological Advancements and Innovations (ICTAI). https://doi.org/10.1109/ictai53825.2021.9673287.

[39] Khan, N.A., Al-Omari, O.M., & Alshahrani, S.M. (2023). An empirical study on the future of publication repositories and its adaptability in public universities—A case study of Shaqra University, Saudi Arabia. In Computational Intelligence: Select Proceedings of InCITe, Pages 823–829. https://doi.org/10.1007/978-981 -19-7346-8_71.

[40] Khan, N.A., & Albatein, J. (2021). COVIBOT – An intelligent WhatsApp based advising bot for COVID-19. In 2021 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE). https://doi. org/10.1109/iccike51210.2021.9410801.

[41] Khan, N.A., & Alshalaan, M. (2025). AI-driven blockchain framework for digital transformation of academic accreditation process: A Saudi Arabian perspective. https://doi.org/10.46759/iijsr.2025.9404.

[42] Khan, N.A., Khan, A.R., & Rajeyyagari, S. (2025). Innovation in teaching and learning with the use of modern computational tools: A post COVID experience. Middle East Journal of Applied Science & Technology, 8(2): 74–82. https://doi.org/10.46431/mejast.2025.8208.

[43] Khan, V.N.A., et al. (2020). Internet of things (IoT) based educational data mining (EDM) system. Journal of Mechanical Control & Mathematical Sciences, 15(3): 271–284. 

[44] Mahafdah, R.F., Al-Omari, O.M., & Khan, N.A. (2018). Learning modal adaptability to improve reading and writing skills of students.

[45] Khan, N.A., et al. (2024). An IoMT enabled iterative artificial bee colony approach using federated learning for detection of heart disease. In Solving with Bees: Transformative Applications of Artificial Bee Colony Algorithm, Pages 103–116. https://doi.org/10.1007/978-981-97-7344-2_6.

[46] Zamani, A.S., Akhtar, M.M., & Khan, N.A. (2025). An application of machine learning, big data and IoT of enterprise architecture: Challenges, solutions and open issues. https://doi.org/10.5772/intechopen.1010260.

Source of Funding:

This study received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Competing Interests Statement:

The authors declare that they have no competing interests related to this work.

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The authors declare that they consented to the publication of this study.

Authors' contributions:

All the authors made an equal contribution in the Conception and design of the work, Data collection, Drafting the article, and Critical revision of the article.

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Authors are willing to share data and material on request.

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Not applicable for this study.

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Acknowledgement:

Authors acknowledge the support and hard work from all those who helped in this study.