Abstract

Conclusion. AI integration offers PTKIN a strategic advantage in achieving sustainability goals and fostering operational excellence. By leveraging internal strengths and external opportunities, and addressing key challenges, these institutions can adopt AI as a transformative tool in advancing Green Campus implementation and long-term ecological sustainability.

Keywords: Artificial Intelligence, Green Campus Implementation, Sustainability, SWOT Analysis

Adel, A. (2024). The convergence of intelligent tutoring, robotics, and IoT in smart education for the transition from industry 4.0 to 5.0. Smart Cities, 7(1), 325–369. https://doi.org/10.3390/smartcities7010014

Ahmad, T., Zhang, D., Huang, C., Zhang, H., Dai, N., Song, Y., & Chen, H. (2021). Artificial intelligence in the sustainable energy industry: Status Quo, challenges, and opportunities. Journal of Cleaner Production, 289, 125834. https://doi.org/10.1016/j.jclepro.2021.125834

Al-Zahrani, A. M. (2024). Harnessing AI for sustainable university practices: toward a greener campus. International Journal of Sustainability in Higher Education. https://doi.org/10.1108/ijshe-08-2024-0566

Alahi, M. E. E., Sukkuea, A., Tina, F. W., Nag, A., Kurdthongmee, W., Suwannarat, K., & Mukhopadhyay, S. C. (2023). Integration of IoT-enabled technologies and artificial intelligence (AI) for smart city scenarios: recent advancements and future trends. Sensors, 23(11), 5206. https://doi.org/10.3390/s23115206

Altassan, A. (2023). Sustainable integration of solar energy, behavior change, and recycling practices in educational institutions: a holistic framework for environmental conservation and quality education. Sustainability, 15(20), 15157. https://doi.org/10.3390/su152015157

Alzoubi, Y. I., & Mishra, A. (2024). Green artificial intelligence initiatives: Potentials and challenges. Journal of Cleaner Production, 143090. https://doi.org/10.1016/j.jclepro.2024.143090

Anthony Jnr, B. (2021). Green campus paradigms for sustainability attainment in higher education institutions–a comparative study. Journal of Science and Technology Policy Management, 12(1), 117–148. https://doi.org/10.1108/jstpm-02-2019-0008

Banala, S. (2024). The Future of IT Operations: Harnessing Cloud Automation for Enhanced Efficiency and The Role of Generative AI Operational Excellence. International Journal of Machine Learning and Artificial Intelligence, 5(5), 1–15.

Biazar, S. M., Golmohammadi, G., Nedhunuri, R. R., Shaghaghi, S., & Mohammadi, K. (2025). Artificial intelligence in hydrology: advancements in soil, water resource management, and sustainable development. Sustainability, 17(5), 2250. https://doi.org/10.3390/su17052250

Cahoy, D. R. (2023). The techno-optimist case for addressing sustainability and its grounding in capitalist (market) incentives. Available at SSRN 4317805.

Cao, F., & Jian, Y. (2024). The Role of integrating AI and VR in fostering environmental awareness and enhancing activism among college students. Science of The Total Environment, 908, 168200. https://doi.org/10.1016/j.scitotenv.2023.168200

Charter, M., & Tischner, U. (2017). Sustainable solutions: developing products and services for the future. Routledge.

Choi, T., Kumar, S., Yue, X., & Chan, H. (2022). Disruptive technologies and operations management in the Industry 4.0 era and beyond. Production and Operations Management, 31(1), 9–31. https://doi.org/10.1111/poms.13622

Chowdhury, S., Budhwar, P., Dey, P. K., Joel-Edgar, S., & Abadie, A. (2022). AI-employee collaboration and business performance: Integrating knowledge-based view, socio-technical systems and organisational socialisation framework. Journal of Business Research, 144, 31–49. https://doi.org/10.1016/j.jbusres.2022.01.069

Cvitanovic, C., McDonald, J., & Hobday, A. J. (2016). From science to action: principles for undertaking environmental research that enables knowledge exchange and evidence-based decision-making. Journal of Environmental Management, 183, 864–874. https://doi.org/10.1016/j.jenvman.2016.09.038

Darko, A., Chan, A. P. C., Ameyaw, E. E., He, B.-J., & Olanipekun, A. O. (2017). Examining issues influencing green building technologies adoption: The United States green building experts’ perspectives. Energy and Buildings, 144, 320–332. https://doi.org/10.1016/j.enbuild.2017.03.060

Debrah, C., Chan, A. P. C., & Darko, A. (2022). Artificial intelligence in green building. Automation in Construction, 137, 104192. https://doi.org/10.1016/j.autcon.2022.104192

Dimitriadou, E., & Lanitis, A. (2023). A critical evaluation, challenges, and future perspectives of using artificial intelligence and emerging technologies in smart classrooms. Smart Learning Environments, 10(1), 12. https://doi.org/10.1186/s40561-023-00231-3

Gao, C., Pan, H., Wang, M., Zhang, T., He, Y., Cheng, J., & Yao, C. (2023). Identifying priority areas for ecological conservation and restoration based on circuit theory and dynamic weighted complex network: A case study of the Sichuan Basin. Ecological Indicators, 155, 111064. https://doi.org/10.1016/j.ecolind.2023.111064

Garimella, S., Lockyear, K., Pharis, D., El Chawa, O., Hughes, M. T., & Kini, G. (2022). Realistic pathways to decarbonization of building energy systems. Joule, 6(5), 956–971. https://doi.org/10.1016/j.joule.2022.04.003

George, B., & Wooden, O. (2023). Managing the strategic transformation of higher education through artificial intelligence. Administrative Sciences, 13(9), 196. https://doi.org/10.3390/admsci13090196

Gültekin, P., Gültekin, Y. S., Başaran, N., & Kaya, M. Y. (2024). Measuring Universities’ sustainability performance with using UI greenmetric world ranking: A case study of Düzce University. Journal of Architectural Sciences and Applications, 9(1), 145–164. https://doi.org/10.30785/mbud.1403115

Gupta, P., Kulkarni, T., & Toksha, B. (2022). AI-Based Predictive Models for Adaptive Learning Systems. In Artificial Intelligence in Higher Education (pp. 113–136). CRC Press. https://doi.org/10.1201/9781003184157-6

Javaherikhah, A., & Sarvari, H. (2025). Implementing Building Information Modeling to Enhance Smart Airport Facility Management: An AHP-SWOT Approach. CivilEng, 6(1), 15. https://doi.org/10.3390/civileng6010015

Khilenko, V. V., Strzelecki, R., & Kotuliak, I. (2018). Solving the problem of dynamic adaptability of artificial intelligence systems that control dynamic technical objects. Cybernetics and Systems Analysis, 54, 867–873. https://doi.org/10.1007/s10559-018-0089-x

Kim, G.-Y., Lee, W.-J., Choi, B., & Lew, Y. K. (2024). Fostering collaborative opportunities for AI start-ups: The case of a hybrid business incubator in Seoul. The Journal of Technology Transfer, 1–30.

Kuleto, V., Ilić, M., Dumangiu, M., Ranković, M., Martins, O. M. D., Păun, D., & Mihoreanu, L. (2021). Exploring opportunities and challenges of artificial intelligence and machine learning in higher education institutions. Sustainability, 13(18), 10424. https://doi.org/10.3390/su131810424

Kulkov, I., Kulkova, J., Rohrbeck, R., Menvielle, L., Kaartemo, V., & Makkonen, H. (2024). Artificial intelligence‐driven sustainable development: Examining organizational, technical, and processing approaches to achieving global goals. Sustainable Development, 32(3), 2253–2267. https://doi.org/10.1002/sd.2773

Lainjo, B. (2023). The The Application of Artificial Intelligence and Machine Learning to Enhance Results-Based Management. Journal of Information Systems and Informatics, 5(4), 1550–1568. https://doi.org/10.51519/journalisi.v5i4.609

Leal Filho, W., Shiel, C., do Paço, A., & Brandli, L. (2015). Putting sustainable development in practice: Campus greening as a tool for institutional sustainability efforts. In Sustainability in higher education (pp. 1–19). Elsevier. https://doi.org/10.1016/b978-0-08-100367-1.00001-9

Leal Filho, W., Vargas, V. R., Salvia, A. L., Brandli, L. L., Pallant, E., Klavins, M., Ray, S., Moggi, S., Maruna, M., Conticelli, E., Ayanore, M. A., Radovic, V., Gupta, B., Sen, S., Paço, A., Michalopoulou, E., Saikim, F. H., Koh, H. L., Frankenberger, F., … Vaccari, M. (2019). The role of higher education institutions in sustainability initiatives at the local level. Journal of Cleaner Production, 233, 1004-1015. https://doi.org/10.1016/j.jclepro.2019.06.059

Lee, S., & Lee, S. (2022). University leadership in climate mitigation: reducing emissions from waste through carbon pricing. International Journal of Sustainability in Higher Education, 23(3), 587–603. https://doi.org/10.1108/ijshe-01-2021-0006

Lo-Iacono-Ferreira, V. G., Capuz-Rizo, S. F., & Torregrosa-López, J. I. (2018). Key Performance Indicators to optimize the environmental performance of Higher Education Institutions with environmental management system–A case study of Universitat Politècnica de València. Journal of Cleaner Production, 178, 846–865. https://doi.org/10.1016/j.jclepro.2017.12.184

Macrae, C. (2024). Managing risk and resilience in autonomous and intelligent systems: Exploring safety in the development, deployment, and use of artificial intelligence in healthcare. Risk Analysis. https://doi.org/10.1111/risa.14273

Mangarin, J. A. (2023). Threats, Opportunities, Weaknesses, and Strengths of the School Management Strategies Used by the Augustinian Recollect (AR) Schools. Online Submission, 1(4), 1–288.

Marinakis, V., Doukas, H., Tsapelas, J., Mouzakitis, S., Sicilia, Á., Madrazo, L., & Sgouridis, S. (2020). From big data to smart energy services: An application for intelligent energy management. Future Generation Computer Systems, 110, 572–586. https://doi.org/10.1016/j.future.2018.04.062

Matarneh, S., Elghaish, F., Rahimian, F. P., Dawood, N., & Edwards, D. (2022). Automated and interconnected facility management system: An open IFC cloud-based BIM solution. Automation in Construction, 143, 104569. https://doi.org/10.1016/j.autcon.2022.104569

McMillan, L., & Varga, L. (2022). A review of the use of artificial intelligence methods in infrastructure systems. Engineering Applications of Artificial Intelligence, 116, 105472. https://doi.org/10.1016/j.engappai.2022.105472

Menon, S., & Suresh, M. (2020). Synergizing education, research, campus operations, and community engagements towards sustainability in higher education: A literature review. International Journal of Sustainability in Higher Education, 21(5), 1015–1051. https://doi.org/10.1108/ijshe-03-2020-0089

Nižetić, S., Djilali, N., Papadopoulos, A., & Rodrigues, J. J. P. C. (2019). Smart technologies for the promotion of energy efficiency, the utilization of sustainable resources, and waste management. Journal of Cleaner Production, 231, 565–591. https://doi.org/10.1016/j.jclepro.2019.04.397

Palomares, I., Martínez-Cámara, E., Montes, R., García-Moral, P., Chiachio, M., Chiachio, J., Alonso, S., Melero, F. J., Molina, D., Fernández, B., Moral, C., Marchena, R., de Vargas, J. P., & Herrera, F. (2021). A panoramic view and swot analysis of artificial intelligence for achieving the sustainable development goals by 2030: progress and prospects. Applied Intelligence, 51(9), 6497–6527. https://doi.org/10.1007/s10489-021-02264-y

Pedro, F., Subosa, M., Rivas, A., & Valverde, P. (2019). Artificial intelligence in education: Challenges and opportunities for sustainable development.

Polin, K., Yigitcanlar, T., Washington, T., & Limb, M. (2024). Unpacking Smart Campus Assessment: Developing a Framework via Narrative Literature Review. Sustainability, 16(6), 2494. https://doi.org/10.3390/su16062494

Pucciarelli, F., & Kaplan, A. (2016). Competition and strategy in higher education: Managing complexity and uncertainty. Business Horizons, 59(3), 311–320. https://doi.org/10.1016/j.bushor.2016.01.003

Rahman, M. H., Mohammed Ghazali, A. B., & Bin Mohamed Sawal, M. Z. H. (2024). Reasons for resistance to technology adoption in university libraries in Bangladesh. Information Development. https://doi.org/10.1177/02666669241294249

Ramos, M. A., Sankaran, K., Guarro, S., Mosleh, A., Ramezani, R., & Arjounilla, A. (2023). The need for and conceptual design of an AI model-based Integrated Flight Advisory System. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 237(2), 485–507. https://doi.org/10.1177/1748006x221083379

Rane, N., Choudhary, S. P., & Rane, J. (2024). Acceptance of artificial intelligence: key factors, challenges, and implementation strategies. Journal of Applied Artificial Intelligence, 5(2), 50–70. https://doi.org/10.48185/jaai.v5i2.1017

Rane, N., Shirke, S., Choudhary, S. P., & Rane, J. (2024). Artificial Intelligence in Education: A SWOT Analysis of ChatGPT and Its Impact on Academic Integrity and Research. Journal of ELT Studies, 1(1), 16–35. https://doi.org/10.48185/jes.v1i1.1315

Reed, J., Van Vianen, J., Deakin, E. L., Barlow, J., & Sunderland, T. (2016). Integrated landscape approaches to managing social and environmental issues in the tropics: learning from the past to guide the future. Global Change Biology, 22(7), 2540–2554. https://doi.org/10.1111/gcb.13284

Rotondo, F., Giovanelli, L., & Ezza, A. (2023). Implementing sustainable innovation in state universities: Process and tools. Journal of Cleaner Production, 391, 136163. https://doi.org/10.1016/j.jclepro.2023.136163

Ryan-Fogarty, Y., O’Carroll, D., O’Mahony, M. J., & O’Regan, B. (2016). Development of the green-campus programme in Ireland: Ensuring continuity of environmental education and action for sustainable development throughout the Irish education system. Teaching Education for Sustainable Development at University Level, 269–284. https://doi.org/10.1007/978-3-319-32928-4_19

Seidel, S., Recker, J., & Brocke, J. v. (2013). Sensemaking and sustainable practicing: Functional affordances of information systems in green transformations. MIS Quarterly, 1275–1299. https://doi.org/10.25300/misq/2013/37.4.13

Strielkowski, W., Grebennikova, V., Lisovskiy, A., Rakhimova, G., & Vasileva, T. (2024). AI‐driven adaptive learning for sustainable educational transformation. Sustainable Development. https://doi.org/10.1002/sd.3221

Taha, A. Z., Mohtar, M., Rahman, M., Periannan, T. M., Jaafar, N. I., & Seng, T. L. (2025). The impact of technology orientation, technology opportunism, and change orientation on the firm operational performance: a moderated-mediation analysis. Operations Management Research, 1–22. https://doi.org/10.1007/s12063-025-00543-2

Tien, P. W., Wei, S., Calautit, J. K., Darkwa, J., & Wood, C. (2022). Real-time monitoring of occupancy activities and window opening within buildings using an integrated deep learning-based approach for reducing energy demand. Applied Energy, 308, 118336. https://doi.org/10.1016/j.apenergy.2021.118336

Tong, A. (2024). The Evolution of AI Engineering: Hardware and Software Dynamics, Historical Progression, Innovations, and Impact on Next-Generation AI Systems. Library Progress International, 44(3), 19715–19737.

UI GreenMetric. (2024). UI GreenMetric World University Rankings 2024. https://greenmetric.ui.ac.id/rankings/overall-rankings-2024

Wazin, W., Patimah, S., & Ansori, A. (2025). Optimizing AI Technology in Assessing Islamic Financing Risks: A SWOT Analysis of Challenges and Opportunities from an Islamic Legal Perspective (Fiqh). Al-Istinbath: Jurnal Hukum Islam, 10(1), 172–193.

Yasuoka, J., Cordeiro, G. A., Brittes, J. L. P., Cooper Ordóñez, R. E., Bajay, S. V., & Nunes, E. (2023). IoT solution for energy management and efficiency on a Brazilian university campus–a case study. International Journal of Sustainability in Higher Education, 24(2), 426–448. https://doi.org/10.1108/ijshe-08-2021-0354

Zavrazhnyi, K. Y. (2024). The impact of the use of artificial intelligence and digital transformation on sustainable business development. Teadmus OÜ.

Zhao, J., & Gómez Fariñas, B. (2023). Artificial intelligence and sustainable decisions. European Business Organization Law Review, 24(1), 1–39. https://doi.org/10.1007/s40804-022-00262-2

Zhong, W., Liu, Y., Dong, K., & Ni, G. (2024). Assessing the synergistic effects of artificial intelligence on pollutant and carbon emission mitigation in China. Energy Economics, 138, 107829. https://doi.org/10.1016/j.eneco.2024.107829