In the heart of Indonesia, a nation grappling with the escalating impacts of climate change, a groundbreaking bibliometric analysis is shedding light on the country’s research landscape concerning climate change adaptation and the role of advanced technologies. Led by Khaidar Ali, a researcher from the Department of Environmental Health at Universitas Jenderal Soedirman, this study, published in the *Journal of Air Pollution and Health* (translated from Indonesian as *Jurnal Pencemaran Udara dan Kesehatan*), is paving the way for innovative solutions in the energy sector and beyond.
The research, which analyzed 1,858 articles from the Scopus database between 2000 and 2023, reveals a significant growth rate of 17.77% in annual publications, indicating a burgeoning interest in climate change adaptation. However, the study also highlights a critical gap: the application of advanced technologies like artificial intelligence (AI), machine learning, and the Internet of Things (IoT) remains relatively unexplored.
“While the research interest in climate change adaptation is elevating each year, the utilization of novel technologies is still in its infancy,” Ali explains. This observation underscores a substantial opportunity for the energy sector, where AI and machine learning can revolutionize predictive capabilities and enhance the management of climate change impacts.
The analysis identified eight clusters of prominent terms, including “climate change,” “adaptation,” “flood,” “remote sensing,” “agriculture,” and “vulnerability.” These terms reflect the current focus of research but also hint at the potential for expansion into more technologically advanced domains. The leading institutions in this field are situated on Java Island, with scholars like Yulianto and Murdiyarso making significant contributions.
The implications for the energy sector are profound. As climate change continues to escalate the risk of extreme weather and the proliferation of infectious and vector-borne diseases, the need for advanced technological solutions becomes increasingly urgent. AI and machine learning can provide comprehensive knowledge, enhance predictive capabilities, and offer innovative solutions to manage these effects.
“Future research on climate change adaptation using advanced technology in Indonesia is needed to provide comprehensive knowledge, enhance predictive capabilities, and provide innovative solutions to manage the effect of climate change,” Ali emphasizes. This call to action resonates with the energy sector, where the integration of AI and machine learning can lead to more efficient and effective climate change adaptation strategies.
As the world looks towards Indonesia for leadership in climate change adaptation, this bibliometric analysis serves as a crucial roadmap. It highlights the current research landscape, identifies gaps, and points the way towards a future where advanced technologies play a pivotal role in mitigating the impacts of climate change. For the energy sector, this means a shift towards more sophisticated, data-driven approaches that can ultimately lead to more sustainable and resilient energy systems.