KLASIFIKASI MAMALIA MENGGUNAKAN EXTREME GRADIENT BOOSTING BERDASARKAN FITUR HISTOGRAM OF ORIENTED GRADIENT
DOI:
https://doi.org/10.36050/betrik.v13i03%20DESEMBER.44Abstract
Mammals are one type of animal that has many characteristics and characteristics. The shape of the face in each type of mammal has a similar shape. The faces of mammals in the form of frontal images are a challenge in image classification. In this study, the Histogram of Oriented Gradient (HOG) is used as a feature of the facial shape of mammals. HOG is used as a strengthening feature in the classification process using the eXtreme Gradient Boosting (XGBoost) method. The test was carried out using a dataset of frontal facial imagery of mammals consisting of 15 species. The results of the tests show that the XGBoost method with the HOG feature is able to provide better classification results for mammals than without the HOG feature. This is indicated by an increase in the precision value of 0.61; recall of 0.62; and an f1-score of 0.60 on XGBoost with HOG feature which is almost double that of XGBoost without HOG feature.
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