Analisis Polusi Cahaya di Indonesia Berdasarkan Parameter Lingkungan Menggunakan Algoritma K-Means Clustering dan Feature Importance
DOI:
https://doi.org/10.54706/senastindo.v7.2025.420Kata Kunci:
Light Pollution, Feature Importance, Polusi CahayaAbstrak
Polusi cahaya merupakan bentuk pencemaran lingkungan yang timbul akibat penggunaan cahaya buatan secara berlebihan dan tidak terarah, yang menyebabkan terganggunya keseimbangan ekologi, kesehatan manusia, serta menurunnya kualitas pengamatan astronomi. Penelitian ini bertujuan untuk menganalisis tingkat polusi cahaya di Indonesia berdasarkan parameter lingkungan menggunakan pendekatan data-driven dengan algoritma K-Means Clustering dan analisis Feature Importance berbasis Decision Tree. Data penelitian diambil dari pengamatan Globe at Night periode 2022–2024 yang mencakup 1.094 observasi di berbagai wilayah Indonesia dengan variabel utama berupa Limiting Magnitude, Cloud Cover, dan Elevation. Tahapan penelitian meliputi proses data preprocessing yang mencakup pembersihan, transformasi variabel kategorikal, serta normalisasi agar hasil analisis lebih valid dan seimbang. Hasil penerapan K-Means menunjukkan bahwa data dapat dikelompokkan menjadi tiga kategori utama, yaitu Cluster 1 sebagai wilayah dengan tingkat polusi cahaya tinggi (ditandai dengan nilai Limiting Magnitude rendah dan Cloud Cover tinggi), Cluster 0 sebagai polusi sedang, dan Cluster 2 sebagai wilayah dengan langit gelap dan polusi cahaya rendah. Analisis Feature Importance mengidentifikasi Cloud Cover sebagai faktor paling dominan dengan kontribusi 0,73, diikuti oleh Limiting Magnitude sebesar 0,27, sedangkan Elevation tidak menunjukkan pengaruh signifikan. Hasil ini menegaskan bahwa faktor meteorologis memiliki pengaruh lebih besar dibanding faktor topografis dalam menentukan intensitas polusi cahaya. Temuan penelitian ini diharapkan menjadi dasar ilmiah dalam perumusan kebijakan mitigasi pencahayaan buatan serta pengelolaan lingkungan malam yang berkelanjutan di Indonesia.
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