Gesang Budiono, . (2023) KLASIFIKASI TEKSTUR NASI BERDASARKAN CITRA BERAS YANG DIGUNAKAN DENGAN METODE CONVOLUTIONAL NEURAL NETWORK. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
There are several types of rice that are commonly sold in rice stores. Currently, many people, especially millennials, are not familiar with the different types of rice. Therefore, digital image processing techniques are needed to help analyze the types of rice. The method commonly used in image processing for image classification is the convolutional neural network (CNN) method. Currently, CNN has shown the most significant results in image classification. This research used a dataset of 1560 rice images. The data was divided into two sets (training data and validation data) with an 80:20 ratio. The accuracy obtained by the CNN model using InceptionV3 for the rice data was 95.7% with a loss of 0.123. The Android application developed in this research achieved an accuracy of 83,4% based on the testing results calculated using the confusion matrix.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | No.Panggil : 1910511090 Pembimbing : Rio Wirawan Penguji 1: Iin Ernawati Penguji 2: Catur Nugrahaeni P. D. |
| Uncontrolled Keywords: | Android, rice, CNN, image, digital, InceptionV3, classification |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
| Depositing User: | Gesang Budiono |
| Date Deposited: | 19 Jul 2023 01:26 |
| Last Modified: | 19 Jul 2023 01:26 |
| URI: | http://repository.upnvj.ac.id/id/eprint/25345 |
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