The extreme volatility and non-linear patterns of Solana (SOL) data, driven by its unique consensus mechanism and massive transaction volume, demand a...
Automatic sign language recognition using deep learning, particularly Convolutional Neural Networks (CNNs), has shown significant potential. The ResNe...
The increasing number and complexity of Android malware require detection systems that are accurate, efficient, and capable of handling high-dimension...
This paper presents a timely and relevant investigation into enhancing Android malware detection, a critical area given the escalating threat landscap...
Chronic Kidney Disease (CKD) is a global health issue characterized by low early detection rates and high diagnostic costs. Artificial intelligence, p...
This study presents a timely and relevant comparative analysis of K-Nearest Neighbor (K-NN) and Naïve Bayes (NB) algorithms for early-stage Chronic Ki...
This study aims to determine how accurate machine learning predictions are for predicting Bitcoin prices using the SVR With RBF Kernel and Random Fore...
Developing automated trading strategies that achieve stable returns while controlling risk remains a central threat in quantitative finance. Many rein...
This paper presents a compelling approach to developing more robust and risk-aware automated stock trading strategies, addressing critical limitations...
The Public Satisfaction Survey (SKM) is an official instrument used by the government to evaluate public service performance as stipulated in Regulati...
This study addresses a pertinent gap in the utilization of Public Satisfaction Survey (SKM) data within government agencies, which traditionally limit...
Student mental health is an important issue that requires a data-driven approach to support the classification process of student depression. This stu...
This study presents a timely and well-structured approach to classifying student depression, a critical issue in contemporary education. The authors e...
Recent developments in deep learning have facilitated the generation of visually convincing deepfake images, creating serious concerns for the reliabi...
This paper presents a timely and relevant contribution to the critical field of deepfake image detection, addressing the growing concerns about the re...
Cyberbullying on Indonesian-language social media has become a serious issue with significant psychological and social consequences, necessitating the...
The paper "Deteksi Cyberbullying pada Komentar Media Sosial Berbahasa Indonesia Menggunakan Pendekatan Hibrida IndoBERTweet-BiLSTM" addresses a highly...
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