Klasifikasi Tutupan Lahan Berdasarkan Random Forest Algorithm Menggunakan Cloud Computing Platform
DOI:
https://doi.org/10.34123/jurnalasks.v14i1.383Keywords:
sustainable development goals, klasifikasi, tutupan lahan, google earth engine, random forestAbstract
Statistik pertanian merupakan salah satu data yang vital di dunia dan memiliki kontribusi besar terhadap pencapaian tujuan program Sustainable Development Goals (SDGs). Dalam SDGs, perhatian terhadap ketahanan pangan difokuskan pada indikator kunci kedua yaitu nol kelaparan (SDG 2). Ketersediaan data tutupan lahan yang akurat diperlukan sebagai data dasar untuk luasan baku sawah yang akan digunakan untuk mengukur tingkat ketahanan pangan. Pemetaan tanaman membutuhkan pemrosesan dan pengelolaan data citra satelit dengan volume yang sangat besar dan tidak terstruktur yang mengarah pada permasalahan Geo Big Data dan menuntut teknologi dan sumber daya baru yang mampu menangani citra satelit dalam jumlah besar. Secara khusus, munculnya sumber daya cloud computing, seperti Google Earth Engine telah mengatasi masalah Geo Big Data ini. Kami menggunakan algoritma Random Forest (RF) pada platform Google Earth Engine (GEE) di Kota Jakarta Utara pada tahun 2019 untuk mengklasifikasikan tutupan lahan. Hasil penelitian menunjukkan bahwa overall accuracy (OA)
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