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Anefia Mutiara Atha
Program Studi Teknik Informatika, Universitas Stikubank Semarang
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering Library & Information Science

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Deteksi Tanaman Herbal Khusus Untuk Penyakit Kulit Dan Penyakit Rambut Menggunakan Convolutional Neural Network (CNN) Dan Tensorflow Anefia Mutiara Atha; Eri Zuliarso
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 14 No 2-a (2022): Jupiter Edisi Oktober 2022
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281./4736/5.jupiter.2022.10

Abstract

Herbal plants are plants with various benefits, one of which can be used to treat diseases naturally, especially skin diseases and hair diseases. Indonesian people are susceptible to skin and hair diseases because Indonesia is a country with a tropical climate. In this modern era, most people are not proficient enough at distinguishing between herbal plants and ordinary plants, which can cause errors in choosing herbal plants. So the researchers specifically made an herbal plant detection system for skin and hair diseases using the Convolutional Neural Network (CNN) model and Tensorflow framework and to help the public recognize herbal plants. The Convolutional Neural Network (CNN) model in this system is used to process two-dimensional data in the form of images. This research uses the Tensorflow framework which functions to run the recognition system. The result of the application test by using the picture of herbal plants can provide the highest accuracy in the sample test reaching 100%, and the average accuracy reaching 93%. So that android-based application is useable to make people easier to identify particular herbal plants for skin and hair diseases.
Co-Authors Eri Zuliarso