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All Journal JURNAL NASIONAL TEKNIK ELEKTRO
Tri Wanda Septian
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Electrical & Electronics Engineering

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Features of Household Solid Waste Object Recognition on Garbage Collector Robot (GACOBOT) Aditya Putra Perdana Prasetyo; Rendyansyah Rendyansyah; Kemahyanto Exaudi; Abdurahman Abdurahman; Tri Wanda Septian
JURNAL NASIONAL TEKNIK ELEKTRO Vol 10, No 3: November 2021
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (761.771 KB) | DOI: 10.25077/jnte.v10n3.834.2021

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.
Co-Authors Aditya Putra Perdana Prasetyo Hanung Adi Nugroho Kemahyanto Exaudi Rendyansyah