<![CDATA[In Indonesia, including in East Java Province, infectious diseases such as Dengue Fever (DHF) and Human Immunodeficiency Virus (HIV) remain public health concerns. Incidence patterns vary by region and time of year. Variations in temporal patterns among districts and cities may lead to suboptimal identification of priority intervention areas when analyses rely solely on absolute case counts. This study aims to analyze the temporal patterns of DHF and HIV case distribution in East Java Province during the 2018–2024 period in order to cluster regions based on similarities in case dynamics over time.The analysis was conducted using a time series clustering approach to group districts and cities according to the similarity of their case development patterns. Temporal similarity was measured using the Dynamic Time Warping method and subsequently clustered using Hierarchical Clustering. Prior to analysis, the data were normalized using the Z-score method to minimize the influence of differences in case scale among regions. The results show that the temporal patterns of DHF and HIV cases were each classified into three main clusters. Cluster quality evaluation using the Silhouette index yielded a value of 0.408 for DHF, indicating a relatively clear cluster structure, whereas a value of 0.197 was obtained for HIV, suggesting a weaker cluster structure due to the complexity and heterogeneity of regional-level case data. Nevertheless, the resulting clusters still provide preliminary information on variations in temporal patterns. The identified clusters represent regions with stable, fluctuating, and increasing case patterns. Several urban areas, such as Pasuruan City, Probolinggo City, and Banyuwangi Regency, tend to belong to clusters with relatively high case levels for more than one disease, indicating challenges in disease control within these regions. These findings provide an initial overview of the temporal dynamics of DHF and HIV cases in East Java, which may serve as supporting evidence for region- and time-based disease control planning.]]>
