Utilizing the UCDP dataset, a conflict event clustering map is made using the K-means algorithm to be analyzed.
In our daily existence, conflict is an inherent and constant aspect, persisting as long as humans continue to engage in social interactions within their communities. Conflict possesses a dual nature in the Western perspective, resembling a "two-sided blade." While it can be advantageous when channeled towards accomplishing tasks, it also holds the potential for calamity if employed in confrontations or battles. This paper's main goal is to use clustering techniques on the "conflict_data_idn" dataset in order to find hidden patterns in the recorded conflicts in Indonesia. It is possible to gain a deeper understanding of the complex dynamics, causal triggers, and contributing factors by classifying conflict events according to shared characteristics. By utilizing the power of data-driven analyses, the study helps to improve decision-making procedures and policy formulation for conflict resolution and prevention.