A Covid-19 Positive Case Prediction and People Movement Restriction Classification DOI Open Access
I Made Artha Agastya

International Journal of Advanced Computer Science and Applications, Год журнала: 2022, Номер 13(8)

Опубликована: Янв. 1, 2022

The world experienced a pandemic that changed people's daily life due to Coronavirus Disease 2019 (covid-19). In Jakarta, the covid-19 cases were discovered on March 18, 2020, and case increased uncontrollably until government conducted movement restriction called pembatasan sosial berskala besar (PSBB). effectivity of was not evaluated in detail. Therefore, we investigated PSBB period understand contribution restriction. Moreover, prediction model is proposed computerize decision models are divided into regression classification models. developed forecast number infected cases. At same time, used identify best type. We utilize data transformation named Principal Component Analysis (PCA) reduce features. our case, method Multiple Linear Regression (MLP). Then, Support Vector Machine (SVM). MLP results 148.38, 37036.37, 0.250336 for Mean Absolute Error (MAE), Square (MSE), R2, respectively. contrast, SVM achieved an accuracy 84.81%. system website successfully deployed.

Язык: Английский

AuSR2: Image watermarking technique for authentication and self-recovery with image texture preservation DOI
Afrig Aminuddin, Ferda Ernawan

Computers & Electrical Engineering, Год журнала: 2022, Номер 102, С. 108207 - 108207

Опубликована: Июнь 30, 2022

Язык: Английский

Процитировано

25

Sentiment Analysis of Covid-19 Vaccination using Support Vector Machine in Indonesia DOI Open Access
Majid Rahardi, Afrig Aminuddin, Ferian Fauzi Abdulloh

и другие.

International Journal of Advanced Computer Science and Applications, Год журнала: 2022, Номер 13(6)

Опубликована: Янв. 1, 2022

Along with the development of Covid-19 pandemic, many responses and news were shared through social media. The new vaccination promoted by government has raised pros cons from public. Public resistance to covid-19 will lead a higher fatality rate. This study carried out sentiment analysis about vaccine using Support Vector Machine (SVM). research aims public response acceptance program. result can be used determine direction policy. Data collection was taken via Twitter in year 2021. data then undergoes preprocessing methods. Afterward, is processed SVM classification. Finally, evaluated confusion matrix. experimental shows that produces 56.80% positive, 33.75% neutral, 9.45% negative. highest model accuracy obtained RBF kernel 92%, linear polynomial kernels 90% accuracy, sigmoid 89% accuracy.

Язык: Английский

Процитировано

24

Software-Defined Networking (SDN): A Review DOI

Quadri Waseem,

Wan Isni Sofiah Wan Din, Afrig Aminuddin

и другие.

2022 5th International Conference on Information and Communications Technology (ICOIACT), Год журнала: 2022, Номер unknown, С. 30 - 35

Опубликована: Авг. 24, 2022

The Internet of Everything (IoE) connects millions machines, vehicles, nodes, smoke detectors, watches, glasses, webcams, and other devices to the internet. These entities need proper guidance control for expected performance. There is always a manage their networks better performance properly. However, managing all these not easy; it big concern. All types network architectures are getting enhanced daily, traditional management process becomes more complex, especially rendering during technology entity modifications. Software-Defined Networking (SDN) extensively used in networks, future technologies (IoT, IoV, 6G, AI, etc.) tackle such concerns issues. as with any new phrase or paradigm, no clear description this has emerged yet, which will give complete understanding SDN, from basic terminology its capabilities. contribution research article significant step forward basics SDN. This proposes detailed review SDN form history, overview, architecture, benefits, services, trends, application, features, challenges.

Язык: Английский

Процитировано

20

ECDSA-based Tamper Detection in Medical Data Using a Watermarking Technique DOI Creative Commons
Ch. Rupa,

Naga Vivek K,

Gautam Srivastava

и другие.

International Journal of Cognitive Computing in Engineering, Год журнала: 2024, Номер 5, С. 78 - 87

Опубликована: Янв. 1, 2024

Telemedicine is a form of healthcare delivery that employs communication technology to provide medical care patients remotely. The use telemedicine has seen significant increase in recent years, presenting challenges such as patient privacy, data security, the need for reliable technology, and potential misdiagnosis without physical examination. Digital Watermarking can assist addressing issues by incorporating unique identifier into image be used authenticate its validity. To tackle these issues, this study proposes robust digital watermarking approach tailored brain images, combining hashing, Elliptic Curve Signature Algorithm (ECDSA), Integer Wavelet Transform-Discrete Cosine Transform (IWT-DCT). This method utilizes Secure Hash (SHA-256) first segment brain's Region Interest (RoI). Subsequently, hashed RoI, along with an ECDSA signature, embedded high-frequency sub-bands using IWT-DCT. embedding process strategically alters coefficients accommodate signature while minimizing perceptual distortion. technique leverages robustness transformed-domain techniques against various attacks combines it SHA-256 integrity authentication purposes. results demonstrate suggested variety processing techniques, including noise addition, filtering, compression maintaining high levels imperceptibility. Key metrics Peak Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE), Structural Similarity Index (SSIM) were evaluate performance. strategy exhibited substantial improvement over existing methods. PSNR increased 68.67, indicating higher quality, MSE reduced 0.96, demonstrating closer pixel values original image. Moreover, SSIM reached 0.98, denoting nearly perfect resemblance between watermarked images. also demonstrated quick extraction speeds, well tamper detection capabilities.

Язык: Английский

Процитировано

4

Observation of Imbalance Tracer Study Data for Graduates Employability Prediction in Indonesia DOI Open Access
Ferian Fauzi Abdulloh, Majid Rahardi, Afrig Aminuddin

и другие.

International Journal of Advanced Computer Science and Applications, Год журнала: 2022, Номер 13(8)

Опубликована: Янв. 1, 2022

Tracer Study is a mandatory aspect of accreditation assessment in Indonesia. The Indonesian Ministry Education requires all Indonesia Universities to anually report graduate tracer study reports the government. also needed by University evaluating success learning that has been applied curriculum. One things need be evaluated level absorption graduates into working industry, so machine model assist Officials and understanding character its graduates, it can help determine curriculum policies. In this research, researcher focuses on making reliable with dataset format determined Government was obtained from Amikom University. study, SVM will tested several variants algorithm handle imbalanced data. compared SMOTE, SMOTE-ENN, SMOTE-Tomek combined detect employability graduates. test carried out K-Fold Cross Validation, highest accuracy precision results produced SMOTE-ENN value 0.96 0.89.

Язык: Английский

Процитировано

13

Deep neural network-based robust hologram watermarking using guided attack module DOI
EunSeong Lee, ZhengHui Piao, Donggyu Sim

и другие.

Expert Systems with Applications, Год журнала: 2024, Номер 249, С. 123486 - 123486

Опубликована: Фев. 14, 2024

Язык: Английский

Процитировано

2

Predictive Models Using Supervised Neural Network for Pollutant Removal Efficiency in Petrochemical Wastewater Treatment DOI
Varun Geetha Mohan, Al-Fahim Mubarak Ali, Mohamed Ariff Ameedeen

и другие.

2022 5th International Conference on Information and Communications Technology (ICOIACT), Год журнала: 2022, Номер unknown, С. 116 - 121

Опубликована: Авг. 24, 2022

The important process in wastewater treatment is the removal of pollutants, and dataset having so many features may cause difficulty training data predicting key variables. This work aims to propose set parameters through normalization techniques, feature selection AI techniques. datasets have 36 a parameter, experimental contain 628. Constant factor, Z-score, Min-max are techniques used normalize petrochemical dataset. SelectKBest, ExtraTreeClassifier, PCA, RFE for mining. Then finally done with implementation help supervised neural network technique called backpropagation (BPNN).

Язык: Английский

Процитировано

9

Sentiment Analysis of Review Sestyc Using Support Vector Machine, Naive Bayes, and Logistic Regression Algorithm DOI

Barka Satya,

Muhammad Hasan S J,

Majid Rahardi

и другие.

2022 5th International Conference on Information and Communications Technology (ICOIACT), Год журнала: 2022, Номер unknown, С. 188 - 193

Опубликована: Авг. 24, 2022

The growth of internet users in Indonesia experiences a very high increase every year, with the also resulting many people using social media. Sestyc is media application created by group millennial children Indonesia. This study was conducted to analyze sentiment text data form review obtained from Google Play Store. purpose this research towards sestyc and find best algorithm for classifying sentiment. used analyzing consists Support Vector Machine, Logistic regression, Naive Bayes. results class labeling on 8000 reviews total 4719 positive 3281 negative reviews. indicate that Machine has highest accuracy value compared other algorithms, where gets an value. 87.81%.

Язык: Английский

Процитировано

9

AuSR3: A new block mapping technique for image authentication and self-recovery to avoid the tamper coincidence problem DOI Creative Commons
Afrig Aminuddin, Ferda Ernawan

Journal of King Saud University - Computer and Information Sciences, Год журнала: 2023, Номер 35(9), С. 101755 - 101755

Опубликована: Сен. 15, 2023

This paper proposes a new block mapping technique for image authentication and self-recovery designed to avoid the tamper coincidence problem called AuSR3. The can arise when modifications an affect original its recovery data, resulting in inability recover tampered region of image. ensures that data is embedded into most distant location possible, minimizing problem. In addition, improved LSB shifting algorithm employed embed watermark consisting data. experimental result shows AuSR3 produce high-quality watermarked images across various datasets with average PSNR values 46.2 dB, which by 2.1 dB compared replacement technique. avoids up 25% tampering rates. It contributes recovered SSIM value 39.10 0.9944, respectively, on 10% rate USC-SIPI dataset.

Язык: Английский

Процитировано

5

A Blind Robust Image Watermarking on Selected DCT Coefficients for Copyright Protection DOI Open Access
Majid Rahardi, Ferian Fauzi Abdulloh, Wahyu Sukestyastama Putra

и другие.

International Journal of Advanced Computer Science and Applications, Год журнала: 2022, Номер 13(7)

Опубликована: Янв. 1, 2022

This paper proposes a blind and robust image watermarking technique using Discrete Cosine Transform (DCT) for copyright protection on color images called BRIW-DCT. Each channel of the host is divided into non-overlapping blocks with size 8×8 pixels. block transformed frequency domain DCT transformation. The watermark embedded by modifying 11th to 15th coefficient. experimental result shows that watermarked achieved high PSNR value 50.4489 dB SSIM 0.9991. Furthermore, various attacks are performed image. BRIW-DCT can successfully recover from tampered image, which produces NC 0.7805 low BER 0.1126.

Язык: Английский

Процитировано

8