IDETIFIKASI UKURAN PAKAIAN BERBASIS IMAGE PROCESSING
Abstract
Data becomes a valuable asset today. With so much data, current technology can open up the possibility to process and make predictions. Machine Learning (ML) is part of Artificial Intelligence (AI) which has become an important tool in software systems in optimizing running systems. Image Classification is one of the topics of Machine Learning that is widely used in machine learning. The application of image classification on the server-side is often done in every complex classification problem because it requires large computing power. This application uses the ml5.js library as a javascript library to process data in machine learning. The application of machine learning for clothing measurement allows users to make it easier to determine the size of clothes at the Reevant Supply IND store. Meanwhile, to support the use of machine learning on the website, a pre-trained model is needed. This study examines neural network settings such as epoch and optimal learning rate. In addition, to prove that you can be superior in training time and loss function values. The results of this study prove that it is easier for users to determine the size of clothes purchased at the Reevant Supply IND store much faster than prior consultation with the store admin
References
Farras, B. (2019, Mei). www.cnbcindonesia.com. Dipetik Februari Kamis, 2021, dari https://www.cnbcindonesia.com/tech/20190513130056-37-72069/mengenal-artificial-intelligence-dan-cara-kerjanya
Gonzales, Rafael C. ; Woods, Richard E. 2002. Digital Image Processing. New Jersey : PrenticeHall, Inc.
Kusumadewi, S. 2003. Artificial Intelligence (Teknik dan Aplikasinya). Yogyakarta: Graha Ilmu
Nurhikmat, T. (2018). Implementasi Deep Learning Untuk Image Classification Menggunakan Algoritma Convolutional Neural Network (Cnn) Pada Citra Wayang Golek. Yogyakarta.
Salamah, U., & Khasanah, F. (2017). Pengujian Sistem Informasi Penjualan Undangan Pernikahan Online Berbasis Web Menggunakan Black Box Testing. Information Management, 35-46.
space.uii.ac.id. (t.thn.). Diambil kembali dari https://dspace.uii.ac.id/bitstream/handle/123456789/7843/TUGAS%20AKHIR_TRIANO%20NURHIKMAT_14611209_STATISTIKA_UII.pdf?sequence=1
Winston dan Prendergast, 1984, The AI Business: The Commercial Uses Of Artificial Intelligence, MIT Press
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