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All Journal Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI)
Prasetia, I Putu Widia
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Computer Science & IT Education Engineering

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Image Classification of Balinese Seasoning Base Genep Based on Deep Learning Prasetia, I Putu Widia; I Made Gede Sunarya
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 13 No. 1 (2024)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v13i1.67967

Abstract

One of Indonesia's abundant natural wealth is spices and seasonings. Base Genep is a basic spice in making traditional Balinese culinary preparations. Base Genep uses many spices and seasonings, including turmeric, ginger, galangal, galangal, candlenuts, nutmeg, pepper, shallots, garlic, coriander, lemongrass, and cloves. From the variety of spices and seasonings that exist in Indonesia, it turns out that the knowledge of the Indonesian people is still low regarding spices and seasonings, especially among the younger generation. This is because these spices/seasonings have characteristics, shapes, and skin colors that are almost similar at first glance, making them difficult to differentiate. Based on these problems, this research was carried out with the aim of helping the public, especially the younger generation, recognize and differentiate types of spices and seasonings. Therefore, in this research, a model based on Deep Learning technology was created. The general objective of this research is to classify spices/seasonings which are often used as basic ingredients in the manufacture of Bumbu Bali Base Genep such as ginger, aromatic ginger, turmeric, and galangal using the YOLOv8 model. The data used in this study were obtained with a smartphone. The data consists of 1200 images consisting of 4 classes. The data is divided into several parts, namely training data, validation and testing data. The resulting dataset is divided into 4 dataset schemes in conducting model training. The highest score for the model in this study was obtained in dataset scheme number 4.
Co-Authors I Made Gede Sunarya