Abstract
Solid waste or garbage is one of the problems that must be faced by the world's population so that life becomes more harmonious. Through a series of studies, a Garbage Collector Robot (GACOBOT) was created which is expected to help humans overcome this problem in terms of garbage collection. By adding a feature in the form of object recognition, the waste can be sorted by type so that it can be grouped and processed further. In this research, using the Support Vector Machine (SVM) classification method based on the feature extraction of the Histogram of Oriented Gradients (HOG) as the main method. Researchers used 14 pieces of data as training data and 10 pieces of data as test data. From the results of the tests that have been carried out, it has been obtained a success rate of 100% that the system has succeeded in separating waste into 2 types, namely plastic bag waste and glass bottle waste.
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