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KLASTERISASI CUACA KOTA PALEMBANG MENGGUNAKAN ALGORITMA K-MEANS (STUDI KASUS: BMKG STASIUN KLIMATOLOGI PALEMBANG)

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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 and SPSS applications 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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Series Title

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Call Number

T759952022

Publisher

Inderalaya : Prodi Sistem Informasi, Fakultas Ilmu Komputer Uniersitas Srwijaya., 2022

Collation

xv, 52 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

005.730 7

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Edition

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Subject(s)

Struktur Data
Prodi Sistem Informasi

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SEPTA

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