Agustini, Siti Lutfia Dwi (2022) Implementasi CNN dalam mendeteksi kematangan mentimun melalui rekognisi citra digital. Sarjana thesis, UIN Sunan Gunung Djati Bandung.
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Abstract
Cucumber has a wide market in Indonesia ranging from traditional markets to modern markets. According to BPS West Java Province in 2016 cucumber production reached 1,400,218 quintals or 140,021.8 tons. The demand for cucumbers from year to year always increases but the availability of cucumbers decreases, this is because the cucumber cultivation factor is still not right. To get cucumber plants starting from optimal cucumber seeds, an optimal level of cucumber maturity is also needed. Determining the maturity level of cucumbers for farmers is a common thing, but this method is often inaccurate due to different perceptions of each person and human visual limitations. This situation becomes an obstacle so that an identification process is needed in the classification to distinguish the two types, namely ripe cucumber and raw cucumber by using the Convolutional Neural Network approach with VGG16. By using this architecture to get good results, namely by getting an accuracy value of 98.5% of the test results by using training data as many as 800 images and 200 images for data testing.
| Item Type: | Thesis (Sarjana) |
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| Uncontrolled Keywords: | Klasifikasi; CNN; VGG16; Mentimun |
| Subjects: | Analysis, Theory of Functions Civil Engineering Technology of Industrial Chemicals Education and Research of Literatures |
| Divisions: | Fakultas Sains dan Teknologi > Program Studi Teknik Informatika |
| Depositing User: | Siti Lutfia Dwi Agustini |
| Date Deposited: | 08 Aug 2022 04:20 |
| Last Modified: | 08 Aug 2022 04:20 |
| URI: | https://etheses.uinsgd.ac.id/id/eprint/54685 |
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