Klasifikasi Tutupan Lahan Berdasarkan Random Forest Algorithm Menggunakan Cloud Computing Platform


Hady Suryono Arif Handoyo Marsuhandi Setia Pramana


The agricultural sector is one of the vital sectors in the world and has a major contribution to the achievement of the goals of the Sustainable Development Goals (SDGs) program. In the SDGs, attention to food security is focused on the second key indicator, namely zero hunger (SDG 2). The availability of accurate land cover data is needed as basic data for the raw area of rice fields that will be used to measure the level of food security. Plant mapping requires the processing and management of very large volumes of unstructured satellite image data which leads to Geo Big Data problems and demands new technology and resources capable of handling large amounts of satellite imagery. In particular, the emergence of cloud computing resources, such as Google Earth Engine, has addressed this Geo Big Data problem. We used the Random Forest (RF) algorithm on the Google Earth Engine (GEE) platform in North Jakarta City in 2019 to classify land cover. The results showed that the overall accuracy (OA)


How to Cite
SURYONO, Hady; MARSUHANDI, Arif Handoyo; PRAMANA, Setia. Klasifikasi Tutupan Lahan Berdasarkan Random Forest Algorithm Menggunakan Cloud Computing Platform. Jurnal Aplikasi Statistika & Komputasi Statistik, [S.l.], v. 14, n. 1, p. 1-12, mar. 2022. ISSN 2615-1367. Available at: <https://jurnal.stis.ac.id/index.php/jurnalasks/article/view/383>. Date accessed: 26 june 2022. doi: https://doi.org/10.34123/jurnalasks.v14i1.383.


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