Identifikasi Jenis Rempah-Rempah Menggunakan Metode CNN Berbasis Android

H Hajriansyah(1*),

(1) Universitas Stikubank, Semarang, Indonesia
(*) Corresponding Author

Abstract


In Indonesia, spices are one of the products of natural wealth that is owned and has been recognized by the world. Spices are parts of plants that have many benefits not only as a complement to spices in cooking, but are also used to boost the immune system. Because there are many types of spices in Indonesia, a system is needed to help people, especially millennials or generation Z, know the various types of spices precisely and clearly. The process of identifying spices is done by using the accuracy calculation on the system using a dataset in the form of images totaling 2700 images and 18 types of spices. The process of identifying spices is generated using the Convolutional Neural Network (CNN) method with the tensorflow module which is used for the training process and data testing. The results of the accuracy experiment on spices produce an accuracy value of recognizing the type of spices by 75%

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References


Tanuwijaya, Evan, and Angelica Roseanne. "Modifikasi Arsitektur VGG16 untuk Klasifikasi Citra Digital Rempah Rempah Indonesia." (2021).

Kaharruddin, Kaharruddin, Kusrini Kusrini, and Emha Taufiq Luthfi. "Klasifikasi Jenis Rempah-Rempah Berdasarkan Fitur Warna Rgb Dan Tekstur Menggunakan Algoritma K-Nearest Neighbor." Informasi Interaktif 4.1 (2019): 17-22.

Hasma, Yunita Aulia, and Widya Silfianti. "Implementasi Deep Learning Menggunakan Framework Tensorflow Dengan Metode Faster Regional Convolutional Neural Network Untuk Pendeteksian Jerawat." Jurnal Ilmiah Teknologi Dan Rekayasa 23.2 (2020): 89-102.

Prastika, Indah Widhi, and Eri Zuliarso. "Deteksi penyakit kulit wajah menggunakan tensorflow dengan metode convolutional neural network." Jurnal Manajemen Informatika dan Sistem Informasi 4.2 (2021): 84-91.

Putra, I. W. S. E. Klasifikasi citra menggunakan convolutional neural network (CNN) pada caltech 101. Diss. Institut Teknologi Sepuluh Nopember, 2016.

Nugroho, Pulung Adi, Indah Fenriana, and Rudy Arijanto. "Implementasi Deep Learning Menggunakan Convolutional Neural Network (Cnn) Pada Ekspresi Manusia." Algor 2.1 (2020): 12-20.

Mulyanto, Agus, et al. "Penerapan Convolutional Neural Network (CNN) pada Pengenalan Aksara Lampung Berbasis Optical Character Recognition (OCR)." JEPIN (Jurnal Edukasi Dan Penelitian Informatika) 7.1 (2021): 52-57.

Prastika, Indah Widhi, and Eri Zuliarso. "Deteksi penyakit kulit wajah menggunakan tensorflow dengan metode convolutional neural network." Jurnal Manajemen Informatika dan Sistem Informasi 4.2 (2021): 84-91.

Choirunisa, Nadia Azahro, Tita Karlita, and Rengga Asmara. "Deteksi Ras Kucing Menggunakan Compound Model Scaling Convolutional Neural Network." Technomedia Journal 6.2 Februari (2022): 236-251.




DOI: http://dx.doi.org/10.30645/jurasik.v8i1.558

DOI (PDF): http://dx.doi.org/10.30645/jurasik.v8i1.558.g536

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