Klasifikasi Citra Cuaca Menggunakan Inception-V3 dan K-Nearest Neighbors

Abstract

Weather imagery has a crucial role in various sectors, such as aviation, maritime and agriculture. Weather conditions have a big impact on activities in these fields and greatly influence operations. Classifying weather images can be done by analyzing weather image data, which can be used to predict the type of weather that may occur. The results of these weather predictions have significant value in daily decision making in these various sectors. One method for classifying weather images can be done by first extracting weather image features using Inception-V3 which is then calculated using the K-Nearest Neighbors method. This research uses 1748 weather images with 4 categories to carry out training which produces a model with Accuracy 91%, F1 91%, Recall 91%, Precision 91%, and uses 8 weather images with 4 categories to carry out testing which produces classifications with all correct values. every image.