Aplikasi Klasifikasi Sampah Organik dan Non Organik dengan Metode GLCM Dan LS-SVM - Joni Wong (Bulletin of Computer Science Research, 2022)
Garbage is an item that no longer has any benefits for its users, which is the residue from the results of daily human activities or is the result of natural processes that have a solid form. The existing waste processing is only limited to conventional waste processing, which is only transported from the waste-producing place to the Temporary Disposal Site (TPS) and then just dumped into the TPS without processing it first, even though the rules for waste management procedures that must be carried out are: waste collection is then recycled and disposed of to the TPS, then the waste is transported to be disposed of at the Final Disposal Site. Therefore, in the process of waste management, it is necessary to separate waste into organic and non-organic waste. However, most people still have difficulty in sorting organic and non-organic waste, so an application is needed to help socialize waste sorting to the community. In this study, the Least Square Support Vector Machine (LS-SVM) method will be used to classify the types of waste. Meanwhile, to perform the texture extraction process from the included garbage image, the Gray Level Co-occurrence Matrix (GLCM) method will be used. The result of this research is a waste classification application that can provide knowledge and add insight for users, especially in distinguishing the types of organic waste and inorganic waste. The application of the GLCM and LS-SVM methods in the built application can detect types of organic and inorganic waste with a success rate of 97%.