Mohammad Dian Purnama, A'Yunin Sofro
The challenging economic conditions following the COVID-19 pandemic have led to widespread economic uncertainty, compounded by the health crisis. Policies have also created psychological and emotional distress that has the potential to trigger criminal acts. Crime has devastating impacts, including loss of life, public disorder, and tarnishing of local reputation. During the post-pandemic period, crime rates in Indonesia have increased, with East Java Province experiencing a 142.26% increase by 2023. This study examines several crime categories: aggravated theft (curat), motor vehicle theft (curanmor), and fraud. The methods used in this research are aggregative nesting (AGNES) and differential analysis clustering (DIANA), with the primary objective of producing a crime level category for each region in East Java Province. The analysis results show that the best clustering results, as validated, show that the DIANA method outperforms the AGNES method for aggravated theft (curat). Both methods yield the same silhouette index for motor vehicle theft (curanmor) and fraud, making either method suitable for these crimes between AGNES and DIANA. One of the results, curat with DIANA method shows that there are 25 regions with low categories, 10 with lower-middle categories, 2 with upper-middle categories, and 1 with high categories. © 2025 Author(s).
Mathematics Department, Universitas Negeri Surabaya, Ketintang, East Java, Surabaya, 60231, Indonesia
