Published: 2025-10-01
Analisis Sistematis Algoritma Convolutional Neural Network untuk Klasifikasi Gambar Bokeh dan Blur: Tinjauan Literatur
DOI: 10.35870/jtik.v9i4.3953
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Abstract
The classification of bokeh and blur images is a challenge in Computer Vision, often addressed using Convolutional Neural Networks (CNNs). This study conducts a Systematic Literature Review (SLR) on 23 articles from Scopus, ScienceDirect, and Google Scholar, with inclusion criteria covering the 2014–2024 publication period, CNN as the primary method, and publication in peer-reviewed journals or conferences (60.87% from scientific journals). The analysis reveals that ResNet and VGG models achieve >90% accuracy, yet still face challenges related to dataset size, computational requirements, and the lack of statistical comparisons across models. This study identifies opportunities for further development through transfer Learning, lightweight models such as MobileNet, and more comprehensive statistical analysis to enhance image classification efficiency across various applications, including digital photography, medical imaging, and security systems.
Keywords
Image Classification ; Deep Learning ; Convolutional Neural Networks ; Computer Vision ; Image Processing
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. 9 No. 4 (2025)
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Section: Computer & Communication Science
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Published: %750 %e, %2025
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License: CC BY 4.0
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Copyright: © 2025 Authors
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DOI: 10.35870/jtik.v9i4.3953
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Alif Chandra Wijaya
Program Studi Mekatronika dan Kecerdasan Buatan, Kampus Purwakarta, Universitas Pendidikan Indonesia, Kota Bandung, Provinsi Jawa Barat, Indonesia.
Arditya Baskara Mahbubi
Program Studi Mekatronika dan Kecerdasan Buatan, Kampus Purwakarta, Universitas Pendidikan Indonesia, Kota Bandung, Provinsi Jawa Barat, Indonesia.
Miftah Fauzi Januarta
Program Studi Mekatronika dan Kecerdasan Buatan, Kampus Purwakarta, Universitas Pendidikan Indonesia, Kota Bandung, Provinsi Jawa Barat, Indonesia.
Tasya Syabila
Program Studi Mekatronika dan Kecerdasan Buatan, Kampus Purwakarta, Universitas Pendidikan Indonesia, Kota Bandung, Provinsi Jawa Barat, Indonesia.
Diky Zakaria
Program Studi Mekatronika dan Kecerdasan Buatan, Kampus Purwakarta, Universitas Pendidikan Indonesia, Kota Bandung, Provinsi Jawa Barat, Indonesia.
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