KLASIFIKASI LEVEL ROASTING PADA BIJI KOPI MENGGUNAKAN ALGORITMA CONVOLUTIONAL NEURAL NETWORK DENGAN ARSITEKTUR RESNET50V2

PAHLEVI, MUHAMMAD RIZA and Miraswan, Kanda Januar and Rizqie, Muhammad Qurhanul (2025) KLASIFIKASI LEVEL ROASTING PADA BIJI KOPI MENGGUNAKAN ALGORITMA CONVOLUTIONAL NEURAL NETWORK DENGAN ARSITEKTUR RESNET50V2. Undergraduate thesis, Sriwijaya University.

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Abstract

Coffee roasting is the process of roasting coffee beans to bring out the aromas and flavors locked inside the beans. Roasted coffee beans are initially green in color which is then roasted in a certain temperature and time which causes the color to change to brown. This research aims to classify the roasting level of coffee beans using convolutional neural network (CNN) algorithm with ResNet50V2 architecture. The roasting levels categorized in this study are unroasted, light roasted, medium roasted and dark roasted. The data used in the model training process consists of 3000 data in image format, with a ratio of 80% training data, 10% testing data and 10% validation data. In addition, 100 image data taken directly from ditaru café were added as additional test data to test the performance of the developed web application model. The total data used in this study amounted to 3100 data. The model performance results were successfully obtained with an average accuracy of 96.62%, precision of 95.80%, recall of 95.75% and F1-score of 95.35%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Roasting Kopi,Convolutional Neural Network, ResNet50V2, klasifikasi
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Muhammad Riza Pahlevi
Date Deposited:	20 May 2025 08:01
Last Modified:	20 May 2025 08:01
URI:	http://repository.unsri.ac.id/id/eprint/173375

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