CNN Modeling for Classification of Bugis Traditional Cakes

Nurul Ahyana; Jeffry Jeffry; Nurul Fadliana; Watty Rimalia; Imran Iskandar

doi:10.61628/jsce.v6i1.1685

Nurul Ahyana Poltekpel Barombong
Jeffry Jeffry Institut Teknologi Bacharuddin Jusuf Habibie
Nurul Fadliana PIP Makassar
Watty Rimalia Universitas Pancasakti
Imran Iskandar

DOI: https://doi.org/10.61628/jsce.v6i1.1685

Keywords: MODEL CNN UNTUK KLASIFIKASI KUE TRADISIONAL BUGIS

Abstract

Abstract

This research aims to create a classification system that can recognize traditional Bugis cakes using the Convolutional Neural Network method. (CNN). Traditional Bugis cakes play an important role in Indonesia's culinary heritage, which is rich in diversity and flavor. However, the lack of documentation and sufficient recognition of these cakes could lead to the loss of cultural knowledge. In this study, a collection of images of traditional Bugis cakes was gathered and processed for training a CNN model. This model was created to recognize and classify various types of cakes based on their visual attributes. The evaluation results show that the CNN model can achieve a high level of accuracy in identifying these cakes, making it a useful tool in preserving and promoting traditional Bugis cakes. This research is expected to contribute to the development of image recognition technology and raise public awareness about the richness of local culinary heritage.

Keywords : Convolutional Neural Network (CNN), Bugis Cake, Indonesian Cuisine

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