Measurement of Centroid Distance in Determining Stunting Clusters

This study aims to develop a vegetable freshness classification model using Convolutional Neural Networks (CNN). The methodology used includes collecting vegetable image datasets, image preprocessing, training CNN models, and evaluating classification accuracy. The dataset used consists of various types of vegetables with varying levels of freshness. The results of the study show that the developed CNN model is able to classify vegetable freshness with high accuracy, so it can assist in the automation process of determining vegetable freshness in the food industry. Model evaluation is carried out using accuracy metrics and mean squared error (MSE).