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Menampilkan 21–28 dari 28 artikel
Butterflies Recognition using Enhanced Transfer Learning and Data Augmentation
Adityawan, Harish Trio
; Farroq, Omar
; Santosa, Stefanus
; Islam, Hussain Md Mehedul
; Sarker, Md Kamruzzaman
; Setiadi, De Rosal Ignatius Moses
Journal of Computing Theories and Applications
Vol 1
, No 2
(2023)
Butterflies’ recognition serves a crucial role as an environmental indicator and a key factor in plant pollination. The automation of this recognition process, facilitated by Convolutional Neural Networks (CNNs), can expedite this task. Several pre-trained CNN models, such as VGG, ResNet, and Inception, have been widely used for this purpose. However, the scope of previous research has been somewhat constrained, focusing only on a maximum of 15 classes. This study proposes to modify the CNN Ince...
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14 Sitasi
Image Encryption using Half-Inverted Cascading Chaos Cipheration
Setiadi, De Rosal Ignatius Moses
; Robet, Robet
; Pribadi, Octara
; Widiono, Suyud
; Sarker, Md Kamruzzaman
Journal of Computing Theories and Applications
Vol 1
, No 2
(2023)
This research introduces an image encryption scheme combining several permutations and substitution-based chaotic techniques, such as Arnold Chaotic Map, 2D-SLMM, 2D-LICM, and 1D-MLM. The proposed method is called Half-Inverted Cascading Chaos Cipheration (HIC3), designed to increase digital image security and confidentiality. The main problem solved is the image's degree of confusion and diffusion. Extensive testing included chi-square analysis, information entropy, NCPCR, UACI, adjacent pixel...
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14 Sitasi
Plant Diseases Classification based Leaves Image using Convolutional Neural Network
Journal of Computing Theories and Applications
Vol 1
, No 1
(2023)
Plant disease is one of the problems in the world of agriculture. Early identification of plant diseases can reduce the risk of loss, so automation is needed to speed up identification. This study proposes a custom-designed convolutional neural network (CNN) model for plant disease recognition. The proposed CNN model is not complex and lightweight, so it can be implemented in model applications. The proposed CNN model consists of 12 CNN layers, which consist of eight layers for feature extractio...
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29 Sitasi
High-Performance Convolutional Neural Network Model to Identify COVID-19 in Medical Images
Journal of Computing Theories and Applications
Vol 1
, No 1
(2023)
Convolutional neural network (CNN) is a deep learning (DL) model that has significantly contributed to medical systems because it is very useful in digital image processing. However, CNN has several limitations, such as being prone to overfitting, not being properly trained if there is data duplication, and can cause unwanted results if there is an imbalance in the amount of data in each class. Data augmentation techniques are used to overcome overfitting, eliminate data duplication, and random...
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25 Sitasi
Comprehensive Analysis and Classification of Skin Diseases based on Image Texture Features using K-Nearest Neighbors Algorithm
Journal of Computing Theories and Applications
Vol 1
, No 1
(2023)
Skin is the largest organ in humans, it functions as the outermost protector of the organs inside. Therefore, the skin is often attacked by various diseases, especially cancer. Skin cancer is divided into two, namely benign and malignant. Malignant has the potential to spread and increase the risk of death. Skin cancer detection traditionally involves time-consuming laboratory tests to determine malignancy or benignity. Therefore, there is a demand for computer-assisted diagnosis through image a...
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25 Sitasi
Dataset and Feature Analysis for Diabetes Mellitus Classification using Random Forest
Mustofa, Fachrul
; Safriandono, Achmad Nuruddin
; Muslikh, Ahmad Rofiqul
; Setiadi, De Rosal Ignatius Moses
Journal of Computing Theories and Applications
Vol 1
, No 1
(2023)
Diabetes Mellitus is a hazardous disease, and according to the World Health Organization (WHO), diabetes will be one of the main causes of death by 2030. One of the most popular diabetes datasets is PIMA Indians, and this dataset has been widely tested on various machine learning (ML) methods, even deep learning (DL). But on average, ML methods are not able to produce good accuracy. The quality of the dataset and features is the most influential thing in this case, so deeper investment is needed...
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36 Sitasi
GLOBALIZATION EFFECT ON PANCASILA VALUES APPLICATION AMONG MILLENNIAL GENERATION
Jurnal Global Citizen : Jurnal Ilmiah Kajian Pendidikan Kewarganegaraan
Vol 10
, No 2
(2021)
Pancasila is taken from the noble values that exist and are well-grown in the life of Indonesian society. It shows that the position of Pancasila itself is the source of all sources of law. This research aims to find out the effect of Pancasila values on the attitudes of the younger generations attitude in this era. Whether the changing period can cause the understanding of Pancasila values has changed during the current development, and it affecting the millennial lifestyle and attitude. This s...
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UJI IMPLEMENTASI ALGORITMA VIOLA-JONES DALAM PENGENALAN WAJAH
Jatmoko, Cahaya
; Setiadi, De Rosal Ignatius Moses
; Hartanto, Danu
; Kurniawan, Alvin Faiz
; Rachmawanto, Eko Hari
; Sari, Christy Atika
; Nilawati, Florentina Esti
Dinamik
Vol 25
, No 2
(2020)
Salah satu algoritma yang sering digunakan untuk melakukan deteksi pada wajah yaitu Viola-Jones. Metode ini merupakan gabungan dari 3 buah fitur yaitu integral image, adaboost dan cascade classifier. Masing-masing fitur mempunyai fungsi tersendiri dan saling melengkapi. Integral image digunakan dalam penentuan ada dan tidaknya gambar, adaboost untuk memilih dan mengatur nilai threshold, sedangkan cascade classifier untuk mengklasifikasi daerah yang akan di deteksi. Untuk memudahkan deteksi, teru...
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