Adrian Triputra, . (2024) RANCANG BANGUN APLIKASI KLASIFIKASI JENIS SAMPAH PLASTIK BERBASIS ANDROID DAN DEEP LEARNING. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
The increasing consumption of plastic presents many problems. Most plastics quickly end up in the trash. Plastic is a non-biodegradable material so improperly disposed plastic waste will pollute the environment for decades or even centuries, leading to plastic pollution. The purpose of this research is to build awareness of plastic waste by creating a plastic waste classification application to educate what types of plastic waste can be recycled and show how to process the plastic simply. The model was created using Convolutional Neural Network (CNN) with Inception V3 architecture. The CNN model was then integrated into an Android application using the Tensorflow Lite (TFLite) library. This research uses the Agile application development method approach because it is flexible in its development. The conclusion of this research is that the CNN model was successfully built using the Inception V3 architecture resulting in a training accuracy of 90.62% and a validation accuracy of 81.25%. The model was successfully integrated into the Android application and allows users to classify the type of plastic waste on the user's device. The results of User Acceptance Testing (UAT) show that the application is very feasible to launch with an average percentage score of 89%. The launch of the app was done using the GitHub platform.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No. Panggil: 2010511037] [Pembimbing 1: Ridwan Raafi'udin] [Pembimbing 2: Nurul Afifah Arifuddin] [Penguji 1: Widya Cholil] [Penguji 2: Ika Nurlaili Isnainiyah] |
| Uncontrolled Keywords: | Plastic Waste, Convolutional Neural Network, Inception V3, Android |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > T Technology (General) |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
| Depositing User: | ADRIAN TRIPUTRA |
| Date Deposited: | 04 Sep 2024 02:31 |
| Last Modified: | 04 Sep 2024 02:31 |
| URI: | http://repository.upnvj.ac.id/id/eprint/30235 |
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