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All Journal Telematika : Jurnal Informatika dan Teknologi Informasi Jurnal Sains dan Teknologi Peternakan Sewagati
Putri, Naimah
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Journal : Telematika : Jurnal Informatika dan Teknologi Informasi

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The Application of Artificial Intelligence in Waste Classification as an Effort In Plastic Waste Management Listyalina, Latifah; Utami, Ratri Retno; Arifin, Uma Fadzilia; Putri, Naimah
Telematika Vol 21, No 1 (2024): Edisi Februari 2024
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v21i1.11977

Abstract

Purpose: Sorting waste before it is deposited in the Final Disposal Site (TPA) is crucial to reduce the increasing amount of waste accumulation each year. This issue can be addressed by implementing machines capable of automatically sorting waste.Design/methodology/approach: This research is quantitative and utilizes secondary data, namely image data of various types of waste. The images will be classified into organic and inorganic waste using a deep learning model. The measurement conducted involves assessing the accuracy of the designed deep learning model in classifying waste images into appropriate categories.Fondings/results: Based on the available dataset, waste identification will be performed, including food waste, paper, wood, leaves, electronic waste, metal, plastic, and bottles. The overall accuracy of the model is 94.42%, indicating that the model correctly classifies 94.42% of waste samples.Originality/value/state of the art: This research can classify 8 types of waste classes successfully using deep learning.
Co-Authors Abdullah, Sofwan Siddiq Adetya, Nais Pinta Asfan, Muhammad Dwi Wulandari Heru Budi Susanto, Heru Budi Jonathan, Sebastian Listyalina, Latifah Lubis, Dina Mariana Uli Nurwantoro Rahmawati, Atiqa Ratri Retno Utami Robbika, Fadzkurisma Tarigan, Deo Steven Barney Uma Fadzilia Arifin, Uma Fadzilia Wibowo, Raden Lukas Martindro Satrio Ari