Fitur Pengkategorian Otomatis dari Gambar Berbasis Web dengan Metode SURF dan Haar Cascade Classifiers

Andrew Samuel (Program Studi Teknik Informatika)
Kartika Gunadi (Program Studi Teknik Informatika)
Justinus Andjarwirawan (Program Studi Teknik Informatika)

Jurnal Infra
Vol 5, No 2 (2017)

Ecommerce is a Market Place and a technological advancement nowadays  where it is now widely used by the public to conducts transaction of needed goods due to very practical. Shopping by using Ecommerce also cheaps and the price is very competitive then conventional store, which more expensive due to large operational costs. But the errors of data contained in Ecommerce is greater than a conventional store, because the data input is depends on the person who using it.With the development of technology, especially on Web Services that helps Ecommerce grow significantly, of course there are solutions to solve the problem and reduce an errors that would made disadvantageous on both side. And one of them is a Computer Intelligence developed to be able to detect and recognize an object.The detection and recognition of objects which will be added on Ecommerce for its feature use frequent of image processing methods for face detection, the Haar Cascade Classifier, and the recognition using SURF. So these feature can improve the performance of Ecommerce so as not to use significant costs and upgrade.