Analysis of Changes in Weather Elements Clustering in Pagar Alam in 2023 and 2024 Using K-Means and Average Linkage Clustering Methods

Climate is a combination of weather elements over a long period of time. Global climate change can impact the productivity of agricultural crops, including coffee plantations in Pagar Alam, South Sumatra, Indonesia. The purpose of this study is to cluster the time of occurrence based on weather elements data in Pagar Alam in 2023 and 2024 using K-means and average linkage clustering methods. The data matrix consists of 53 weeks and 15 weather element variables. Based on the biplot and Silhouette Index results of both data matrices, the K values used were 2 and 4. The K-means clustering results on the 2024 data matrix indicate that a cluster of the majority of weeks is characterized by higher minimum temperature, dew point, humidity, precipitation cover, and cloud cover. Meanwhile, in the 2023 data matrix, a cluster of the majority of weeks is characterized by high levels of dew, humidity, and cloud cover. The average linkage clustering results are almost similar to the K-means clustering results. The results of time data clustering can help develop strategies for timing agricultural land management practices as an adaptation measure to weather variability.