CLUSTERING ANALYSIS OF SIGNIFICANT WAVE HEIGHT DYNAMICS USING K-MEANS ALGORITHM IN THE SEMARANG–DEMAK COASTAL WATERS - Wahyu Sri Mulyani; Aji Supriyanto (Program Studi Teknik Informatika Universitas Khairun, 2025)
Global climate change has led to an increase in the frequency and intensity of extreme events at sea, including in the Semarang-Demak coastal area. This region is highly vulnerable to the dynamics of Significant Wave Height (SWH), sea level rise, and coastal land subsidence. As a result, in addition to disrupting maritime navigation, frequent occurrences of tidal flooding (rob) have caused significant disturbances to economic activities and settlements in the coastal area. This study aims to develop a clustering model for SWH in the Semarang-Demak waters using the K-Means algorithm. The data used includes oceanographic and meteorological parameters from the Tanjung Emas Semarang Maritime Meteorological Station (BMKG) for the period 2019-2024. The clustering results show that K-Means successfully formed three clusters of sea waves representing calm, moderate, and high waves. Model evaluation using the Silhouette Score with a value of 0.725 and the Davies-Bouldin Index (DBI) of 0.425 indicates good performance, with K=3 as the optimal cluster. Temporal analysis reveals a clear seasonal pattern, where high energy conditions dominate during the west season (December-February), while calm conditions are prevalent during the east season (June-August). These findings provide a foundation for early warning systems and disaster risk management in this region, with further clustering tests using other algorithms and the need for improved data quality.