Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer
Vol 13 No 3 (2022): JURNAL ILMIAH BETRIK : Besemah Teknologi Informasi dan Komputer

KLASIFIKASI MAMALIA MENGGUNAKAN EXTREME GRADIENT BOOSTING BERDASARKAN FITUR HISTOGRAM OF ORIENTED GRADIENT

Yohannes Yohannes (Universitas Multi Data Palembang)
Johannes Petrus (Universitas Multi Data Palembang)



Article Info

Publish Date
16 Dec 2022

Abstract

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 value of precision, recall, and f1-score on XGBoost with the HOG feature which is almost twice as high as XGBoost without the HOG feature.

Copyrights © 2022






Journal Info

Abbrev

betrik

Publisher

Subject

Computer Science & IT

Description

Besemah Informatika dan Teknologi Komputer (BETRIK) adalah jurnal nasional yang diterbitkan oleh Lembaga Penelitian dan Layanan (LPPM), Sekolah Tinggi Teknologi Pagar Alam (STTP). Karya ilmiah ini diterbitkan sebanyak 6 manuskrip, dengan topik yang berkaitan dengan masalah Teknologi Informasi dan ...