On Friday, October 11, 2024, a Focus Group Discussion (FGD) on the DBSCAN Clustering Model in Machine Learning was held online via Zoom. The event featured three prominent speakers: Prof. Stalin Selvaraj from Sastra Deemed University, Prof. Drs. Dafik, M.Sc., Ph.D. from the PUI-PT Combinatorics and Graph, University of Jember, and Falih Gozi Febrinanto from Federation University Australia. The FGD aimed to discuss various innovative approaches to using the DBSCAN clustering model. Participants included academics, researchers, and practitioners eager to engage in the discussion. The event was well-received by those interested in the latest developments in machine learning technology.

During the FGD, Prof. Stalin Selvaraj presented on the application of DBSCAN in biosensor technology. He explained how DBSCAN can be used to detect patterns and anomalies in biosensor data, which is crucial for advancing healthcare technologies. Meanwhile, Prof. Drs. Dafik explored the use of graph embedding approaches, such as node2vec, in applying DBSCAN to understand complex graphical data structures. He elaborated on how this integration can improve clustering accuracy. These topics provided fresh insights into optimizing DBSCAN for various sectors.

The discussion continued with Falih Gozi Febrinanto from Federation University Australia, who explained BARGAIN (Balanced Graph Structure for Brains) clustering using Graph Convolution Network for brain structure mapping. Falih demonstrated how this method can handle complex data relevant to brain research. The combination of DBSCAN and Graph Convolution Network technology offers effective solutions for managing large and intricate datasets. Participants actively engaged in discussions about the potential applications of this method in other research areas. This FGD successfully provided an in-depth look into innovative and practical advancements in clustering techniques.