Abstract
Weather related information is one of the things that is very important and has a big influence on all kinds of life activities such as in public safety, socio-economics, agriculture, aviation, and so on.The weather in each place or region is different, this happens because of the different weather elements in each place/region. By using data mining clustering techniques, weather clustering will be carried out in the city of Palembang. K-means is the algorithm chosen for clustering the weather in the city of Palembang. The test was carried out using daily weather data for 2020-2021 from BMKG by utilizing rapidminer application as learning techniques for data. So that we will get a group of weather characteristics of Palembang city based on similarities and dissimilarities. From the test results, the best k was obtained at k=3 with the parameters Measure Types ( NumericalMeasure ) and Divergences ( DynamicTimeWarpingDistance ) as well as a local random seed of 2500 seen from the results of the Davies-Bouldin Index (DBI). This weather grouping can later provide information on how the weather character is and reduce the impact of sudden changes in weather conditions.
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