Penerapan K-Means untuk Klasterisasi Pola Cuaca Spasial di Kawasan Sumatera Berbasis Data Reanalisis ERA5
DOI:
https://doi.org/10.62712/juktisi.v5i1.945Keywords:
K-Means, ERA5, Klasterisasi, Pola Cuaca, Data MiningAbstract
Penelitian ini bertujuan untuk mengelompokkan pola cuaca spasial di wilayah Sumatera dengan memanfaatkan metode K-Means berbasis data reanalisis ERA5. Latar belakang penelitian ini didasari oleh kompleksitas dinamika cuaca yang tinggi serta keterbatasan data observasi yang tersebar tidak merata, sehingga diperlukan pendekatan berbasis data untuk memperoleh pola yang lebih jelas dan terstruktur. Proses penelitian dilakukan melalui beberapa tahapan, yaitu pembersihan data, normalisasi menggunakan metode Min-Max Scaling, penentuan jumlah cluster dengan metode Elbow, serta proses pengelompokan menggunakan algoritma K-Means. Variabel yang digunakan meliputi suhu udara, tekanan permukaan, dan kecepatan angin sebagai representasi kondisi atmosfer. Hasil penelitian menunjukkan bahwa pengelompokan yang dihasilkan mampu menggambarkan perbedaan karakteristik wilayah, seperti area perairan, pegunungan, dataran rendah, serta zona transisi pesisir. Selain itu, pola yang terbentuk juga mencerminkan kondisi geografis yang beragam di wilayah penelitian. Dengan demikian, metode K-Means dapat digunakan sebagai pendekatan yang efektif dalam mengidentifikasi pola cuaca spasial secara lebih sistematis.
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