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Olvy Diaz Annesa
Institut Teknologi Telkom Purwokerto
Computer Science & IT Engineering

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Identifikasi Spesies Reptil Menggunakan Convolutional Neural Network (CNN) Olvy Diaz Annesa; Condro Kartiko; Agi Prasetiadi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 5 (2020): Oktober 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1430.695 KB) | DOI: 10.29207/resti.v4i5.2282

Abstract

Reptiles are one of the most common fauna in the territory of Indonesia. quite a lot of people who have an interest in knowing more about this fauna in order to increase knowledge. Based on previous research, Deep Learning is needed in particular the CNN method for computer programs to identify reptile species through images. This reseacrh aims to determine the right model in producing high accuracy in the identification of reptile species. Thousands of images are generated through data augmentation processes for manually captured images. Using the Python programming language and Dropout technique, an accuracy of 93% was obtained by this research in identifying 14 different types of reptiles.
Co-Authors Agi Prasetiadi Condro Kartiko