RANCANG BANGUN APLIKASI DETEKSI JENIS SAMPAH ORGANIK DAN SAMPAH DAUR ULANG DENGAN MENGGUNAKAN MODEL RESNET-50 BERBASIS ANDROID

Abednego Christianyoel Rumagit, . (2024) RANCANG BANGUN APLIKASI DETEKSI JENIS SAMPAH ORGANIK DAN SAMPAH DAUR ULANG DENGAN MENGGUNAKAN MODEL RESNET-50 BERBASIS ANDROID. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

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Abstract

The increasing waste management problem in Indonesia's urban areas is a serious challenge in overcoming environmental pollution. The purpose of this research is to overcome the challenges in the waste sorting and management process by developing an Android application that uses the ResNet-50 model to classify organic and recyclable waste and provide ways to recycle the waste. This application aims to increase public awareness and simplify the waste sorting process. Researchers built the ResNet-50 model using Transfer Learning techniques to classify organic and recycled waste which was then integrated into an Android application using TF Lite (TensorFlow Lite). The method used by researchers in this research is the Waterfall method. Researchers use the Waterfall method to develop Android application systems by following a structured sequence of stages, starting from needs analysis to system maintenance. The conclusion of this research is that the Deep Learning model using ResNet-50 architecture was successfully built with 99% training accuracy, 96% validation, and 94% testing. In addition, the Eco-Detect Android application development process uses the Waterfall method through requirements analysis, system design, implementation, testing, and system maintenance. The integration of the ResNet-50 model into the application enables offline waste detection. The results of application testing using the UAT (User Acceptance Testing) method show a high level of user satisfaction, with an average score of 91%.

Item Type: Thesis (Skripsi)
Additional Information: [No.Panggil: 2010511042] [Pembimbing 1: Ridwan Raafi’udin] [Pembimbing 2: Nindy Irzavika] [Penguji 1: Indra Permana Solihin] [Penguji 2: Zatin Niqotaini]
Uncontrolled Keywords: Waste, Deep Learning, Transfer Learning, ResNet-50, Android
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Fakultas Ilmu Komputer > Program Studi Informatika (S1)
Depositing User: ABEDNEGO CHRISTIANYOEL RUMAGIT
Date Deposited: 05 Sep 2024 04:46
Last Modified: 05 Sep 2024 04:46
URI: http://repository.upnvj.ac.id/id/eprint/30214

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