Putra, Febby Andika (2025) PENERAPAN METODE NAÏVE BAYES DAN CONVOLUTIONAL NEURAL NETWORK DALAM KLASIFIKASI KESEGARAN IKAN MUNGKUS BERDASARKAN CITRA MATA DAN INSANG IKAN. Skripsi (Bachelor) thesis, Universitas Muhammadiyah Bengkulu.
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Abstract
The mungkus fish (Sicyopterus stimpsoni) is a species of freshwater fish that is a typical mascot of Kaur Regency, Bengkulu Province. This fish lives in clear, fast-flowing waters and is known for its ability to attach to rocks using a special structure on its stomach called a cupak. Mungkus fish has high economic value and is consumed daily by the local community. However, the high demand is not balanced by adequate availability, resulting in increasing prices. In addition, the lack of public knowledge regarding the assessment of fish freshness causes the risk of consuming fish that is not fresh, which has the potential to endanger health. Traditional assessment of fish freshness based on physical parameters such as eyes, gills, and meat texture is considered less accurate and requires special expertise. Therefore, this study proposes the use of the Naïve Bayes and Convolutional Neural Network (CNN) methods to classify the freshness of mungkus fish based on eye and gill images. Naïve Bayes works based on Bayes' Theorem with the assumption of independence between features, while CNN is able to extract complex features from images without the need for manual extraction. The application of these two methods is expected to provide an objective, efficient, and accurate solution in assessing the freshness of mungkus fish, and be beneficial for fishermen and consumers.
| Item Type: | Thesis (Skripsi (Bachelor)) |
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| Additional Information: | Pembimbing : Yulia Darnita, S.Kom., M.Kom. |
| Uncontrolled Keywords: | Classification, Fish Freshness, Naïve Bayes, CNN |
| Subjects: | Universitas Muhammadiyah Bengkulu > 02-Fakultas Teknik > 55201-(S1) Teknik Informatika 02-Fakultas Teknik > 55201-(S1) Teknik Informatika |
| Divisions: | 02-Fakultas Teknik > 55201-(S1) Teknik Informatika Subjek Terkait > 02-Fakultas Teknik > 55201-(S1) Teknik Informatika |
| Depositing User: | Mr Andeska Ulok Kupai |
| Date Deposited: | 22 Sep 2025 04:02 |
| Last Modified: | 22 Sep 2025 04:02 |
| URI: | http://repository.umb.ac.id/id/eprint/1476 |
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