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All Journal JURIKOM (Jurnal Riset Komputer)
Miftahuddin Fahmi
Universitas Ahmad Dahlan, Yogyakarta
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Pemilahan Sampah Menggunakan Model Klasifikasi Support Vector Machine Gabungan dengan Convolutional Neural Network Miftahuddin Fahmi; Anton Yudhana; Sunardi Sunardi
JURIKOM (Jurnal Riset Komputer) Vol 10, No 1 (2023): Februari 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v10i1.5468

Abstract

Waste sorting is a vital process in waste management. The problem with the waste sorting process is that humans feel uncomfortable with the smell of garbage for too long. The problem can be solved by creating a machine learning system to identify the waste type. The purpose of this research is to solve waste management problems using machine learning using the most accurate classification model. The types of wastein this research are limited to only two types: organic and inorganic. Data was collected and revised from the Kaggle dataset. Data were imported into the system using Python. Data was trained and used for classifying the waste based on the image source. Waste images will be determined in their category using the Support Vector Machine model with feature extraction using the Convolution layer. The system successfully performs waste classification using the Support Vector Machine model combined with the Convolutional Neural Network with an accuracy of 96,16% and a loss of 7,25% on the overall category
Co-Authors Anton Yudhana Sunardi, Sunardi