Published: 2024-04-01
Klasifikasi Gambar Pemandangan dengan Kecerdasan Buatan Berbasis CNN
DOI: 10.35870/jtik.v8i2.1424
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Abstract
The use of Artificial Intelligence based on Convolutional Neural Network (CNN) has made remarkable advancements in visual analysis, particularly in landscape image classification. This study applies the CNN method to automatically classify landscape images. Through sophisticated network training and feature extraction steps, CNN can recognize unique patterns and features from various landscape categories, such as mountains, forests, streets, seas, and glaciers. The key advantage of CNN lies in its ability to identify complex and abstract features in images. The evaluation results show that the CNN model achieves satisfying accuracy in classifying landscape images. The application of this method offers practical benefits in various areas, including location recognition, virtual travel, and environmental analysis. AI based on CNN opens new possibilities in visual landscape recognition and its potential to contribute to automated understanding of the beauty of nature
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Article Information
This article has been peer-reviewed and published in the Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi). The content is available under the terms of the Creative Commons Attribution 4.0 International License.
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Issue: Vol. 8 No. 2 (2024)
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Section: Computer & Communication Science
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Published: %750 %e, %2024
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License: CC BY 4.0
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Copyright: © 2024 Authors
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DOI: 10.35870/jtik.v8i2.1424
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Mozes Hasian Veltin Sinaga
Program Studi Sistem Informasi, Fakultas Informatika, Institut Teknologi Telkom Purwokerto, Kota Purwokerto, Kabupaten Banyumas, Provinsi Jawa Tengah, Indonesia
Muhammad Albirra
Program Studi Sistem Informasi, Fakultas Informatika, Institut Teknologi Telkom Purwokerto, Kota Purwokerto, Kabupaten Banyumas, Provinsi Jawa Tengah, Indonesia
Muhammad Fajar Sidiq
Program Studi Sistem Informasi, Fakultas Informatika, Institut Teknologi Telkom Purwokerto, Kota Purwokerto, Kabupaten Banyumas, Provinsi Jawa Tengah, Indonesia
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