<![CDATA[Land cover information is very important information to describe a phenomenon from various aspects that occur on the earth's surface. Land cover information can be obtained using remote sensing technology which can provide spatial information on the earth's surface quickly and precisely, one of the methods used is supervised classification. The rapid development of technology has an impact on satellite image processing methods, one of which is the Google Earth Engine (GEE). This cloud computing-based platform allows users to process satellite images that can be accessed online and free. The conventional method that is commonly used in land cover classification takes a long time because the process of downloading satellite image data must be carried out and continued with data processing using satellite image processing software, otherwise, a computer that has high performance is required so that the image processing process can run smoothly. GEE provides convenience because processing can be done anywhere and anytime without being limited by hardware specifications which often become obstacles in conventional satellite image processing. This study aims to classify land cover using the cloud computation method found in GEE. The level of confidence in the results of the land cover classification was tested using the confusion matrix. The result of the accuracy shows that the overall accuracy level is 96.458% and the kappa accuracy is 93.851%. The classification results show that image processing based on GEE cloud computing can produce a good land cover classification. ]]>
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