Analisis Spasio-Temporal Multi-Sensor NASA Menggunakan Algoritma K-Means untuk Zonasi Potensi Kesehatan Tanaman di Wilayah Sumatera
DOI:
https://doi.org/10.62712/juktisi.v5i2.934Keywords:
Remote Sensing, EVI, Land Surface Temperature, Rainfall, K-Means Clustering, Plant HealthAbstract
Penelitian ini bertujuan untuk menganalisis zonasi potensi kesehatan tanaman di wilayah Pulau Sumatera menggunakan pendekatan analisis spasio-temporal berbasis data satelit multi-sensor. Data yang digunakan meliputi Enhanced Vegetation Index (EVI) dari produk MOD13Q1, Land Surface Temperature (LST) dari produk MOD11A1, serta data curah hujan dari produk GPM IMERG. Seluruh data satelit diproses melalui tahapan pra-pemrosesan yang mencakup ekstraksi data, mosaicking citra, penyelarasan sistem koordinat, resampling spasial, serta pembersihan data untuk menghilangkan piksel anomali. Data yang telah diproses kemudian dianalisis menggunakan algoritma K-Means Clustering untuk mengelompokkan wilayah berdasarkan kemiripan karakteristik lingkungan. Penentuan jumlah cluster optimal dilakukan menggunakan metode Elbow Method, sedangkan kualitas pengelompokan dievaluasi menggunakan Silhouette Score. Hasil penelitian menunjukkan bahwa jumlah cluster optimal adalah enam zona yang merepresentasikan variasi kondisi biofisik wilayah Sumatera, yaitu dataran rendah dengan vegetasi lebat, lahan terbuka atau terdegradasi, dataran basah dengan curah hujan tinggi, dataran pesisir dengan suhu tinggi, wilayah pegunungan dengan suhu rendah, serta wilayah lereng pegunungan sebagai zona transisi. Analisis terhadap lebih dari dua juta piksel observasi menghasilkan nilai Silhouette Score sebesar 0,2739 yang menunjukkan bahwa struktur cluster telah terbentuk dengan cukup baik. Hasil zonasi ini memberikan gambaran spasial mengenai potensi kesehatan tanaman di Pulau Sumatera dan dapat dimanfaatkan sebagai dasar dalam perencanaan pengelolaan lahan serta pengembangan sistem pertanian yang lebih adaptif terhadap kondisi lingkungan.
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Copyright (c) 2026 Yusrida Jelianti Sihite, Yohanes Gerardus Haga Zai , Andika Veriando Saragih
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