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All Journal Jusikom: Jurnal Sistem Informasi Ilmu Komputer
Sinaga, Maria Riska Ratna Sari
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Decision Sciences, Operations Research & Management

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Herbal Leaf Image Classification Using Convolutional Neural Network (CNN) Mujahid, Putra Edi; Manik, Rosianni; Simbolon, Junpri Sardodo; Sinaga, Maria Riska Ratna Sari; Aisyah, Siti; Nababan, Marlince; Harmaja, Okta Jaya
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 8 No. 1 (2024): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v8i1.5145

Abstract

This research delves into the application of Convolutional Neural Networks (CNNs) to address the complexities of identifying herbal leaf species in Indonesia, often challenging due to the vast variations in shape, color, and texture. Utilizing a dataset of herbal leaf images acquired using the Bing Downloader Scrapping technique, a CNN model was trained to classify various plant varieties with a remarkable accuracy rate of 92.66%. Additionally, the analysis of low loss values indicates that the model not only effectively maps the intricate features of each image to the correct category but also efficiently reduces error rates. These findings offer a significant contribution to the context of herbal medicine development and biodiversity conservation, opening up avenues for technological integration in efforts to preserve Indonesia's natural and cultural resources.
Co-Authors Manik, Rosianni Mujahid, Putra Edi Nababan, Marlince Okta Jaya Harmaja Simbolon, Junpri Sardodo Siti Aisyah