PENERAPAN ALGORITMA K-MEANS UNTUK KLASTERISASI POLA IKLIM STUDI KASUS: PROVINSI JAMBI PERIODE 2020-2024

Yandi Anzari; Yonggi Puriza; Niko Akbar; Nurul Abdillah; Oki Dahwanu; Elsi Alfionita Syawal

doi:10.46576/djtechno.v6i3.7994

PENERAPAN ALGORITMA K-MEANS UNTUK KLASTERISASI POLA IKLIM STUDI KASUS: PROVINSI JAMBI PERIODE 2020-2024

Yandi Anzari, Yonggi Puriza, Niko Akbar, Nurul Abdillah, Oki Dahwanu, Elsi Alfionita Syawal

Abstract

Penelitian ini menerapkan algoritma K‑Means untuk mengidentifikasi pola iklim dominan di Provinsi Jambi pada periode Januari 2020 sampai Desember 2024. Dataset bulanan berjumlah 60 observasi yang memuat enam variabel meteorologi: curah hujan, suhu rata‑rata, suhu maksimum, suhu minimum, kecepatan angin, dan kelembaban relatif. Data diagregasi dari data harian menjadi bulanan dan dipra‑proses dengan standardisasi Z‑Score untuk mengatasi heterogenitas skala antar fitur. Penentuan jumlah klaster optimal dilakukan secara kuantitatif menggunakan Elbow Method berdasarkan nilai inersia, yang menunjukkan titik belok pada k=3. Model K‑Means diinisialisasi secara acak dan dijalankan dengan beberapa pengulangan untuk menilai stabilitas hasil; keluaran divisualisasikan dalam proyeksi 2D dan 3D untuk memudahkan interpretasi spasial. Analisis centroid mengidentifikasi tiga rezim iklim: rezim kering/transisi (curah hujan rendah dan suhu relatif tinggi), rezim monsonal normal (curah hujan menengah‑tinggi dan kelembaban tinggi), serta rezim basah ekstrem (curah hujan sangat tinggi dan kelembaban tinggi). Hasil ini menyediakan tipologi iklim berbasis data yang relevan untuk perencanaan pertanian, mitigasi bencana hidrometeorologi, dan kebijakan adaptasi iklim di tingkat provinsi.

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DOI: https://doi.org/10.46576/djtechno.v6i3.7994