This study aims to classify the popularity of Korean dramas based on ratings obtained from the MyDramaList website. With the rapid growth of digital entertainment platforms, evaluating drama popularity has become increasingly important for understanding audience preferences and supporting decision-making in the content industry. The Naive Bayes algorithm is employed as the...
Perkembangan industri ritel, khususnya pada sektor perlengkapan rumah tangga (houseware), mendorong meningkatnya persaingan pasar sehingga menuntut pelaku usaha untuk menerapkan strategi pengelolaan produk yang lebih efektif dan berbasis data. Winnie Houseware menghadapi permasalahan dalam menentukan produk unggulan yang layak dijadikan prioritas etalase, karena proses...
Fraud detection has become a critical concern for financial institutions seeking to safeguard their assets and maintain client trust in an increasingly digitized financial landscape. This study examines the application of machine learning (ML) techniques to enhance fraud detection systems within financial institutions. By leveraging computational algorithms and data analytics...
The evolution of algorithmic trading (AT) has dramatically transformed the Foreign Exchange (Forex) market by integrating computational intelligence into trading and decision-making processes. Despite these advancements, Malaysian traders remain challenged in adopting such systems, particularly due to limited technical expertise, inadequate adaptation to local trading practices...
Player retention is the primary economic driver in the Free-to-Play (F2P) gaming industry, yet traditional churn prediction methodologies often rely solely on binary classification, neglecting the critical temporal dimension of when a player is likely to leave. Furthermore, the scarcity of open-source behavioral datasets restricts the development of reproducible academic...
Project performance remains a persistent challenge in Malaysia’s oil and gas industry, where cost overruns, schedule delays, and operational inefficiencies continue to occur despite extensive prior research. Although earlier studies have examined organizational, technological, and environmental determinants, limited attention has been given to how these dimensions interact to...
Phishing attacks continue to be one of the most pervasive cybersecurity threats, particularly through malicious URLs designed to mimic legitimate websites and steal sensitive user information. To address this challenge, this study employs the Random Forest algorithm for automated phishing URL detection using a publicly available dataset from Kaggle. The dataset contains diverse...
Penyakit jantung merupakan penyebab kematian tertinggi di dunia. Deteksi dini risiko penyakit jantung dapat dilakukan menggunakan algoritma Framingham Risk Score (FRS). Penelitian ini merancang sistem prediksi risiko penyakit jantung berbasis web dengan mengadaptasi algortima Framingham Risk Score (FRS) yang dimodifikasi untuk lingkungan digital. Sistem dirancang menggunakan HTML...
Document layout analysis plays a critical role in the digitization pipeline by identifying, segmenting, and classifying structural elements within documents to support accurate information extraction. This task becomes increasingly challenging when dealing with heterogeneous layouts that contain paragraphs, tables, figures, mathematical expressions, and other visual components...
Diabetes mellitus is a global chronic metabolic disease that poses a serious threat to human health. Accurate and early prediction of diabetes is essential for effective medical treatment and long-term disease management. In this study, we propose a deep learning–based framework as a novel approach for diabetes prediction using a large-scale dataset containing more than 6,000...
Cryptography is a scientific discipline used to protect information by transforming readable messages into forms that are unintelligible to unauthorized parties. One of the earliest and simplest cryptographic techniques is the Caesar Cipher, which remains relevant for academic exploration, particularly in understanding fundamental concepts of substitution ciphers. This study...
Electronic Health Records (EHRs) are essential to modern healthcare infrastructure, yet they face persistent challenges related to data security, interoperability, and unauthorized access. Blockchain technology, through its use of cryptographic protocols, smart contracts, and consensus mechanisms, offers a decentralized and tamper-resistant solution for managing EHRs. This paper...
Network bandwidth management using log data is a challenging task, especially in anomaly detection, e.g., fraudulent bandwidth that violates the Service Level Agreement (SLA). The present study suggests a deep learning automatic classification method for network logs, which leverages the Gated Recurrent Unit (GRU) and is used in time-series tensor configurations given as [N, 5...
Cell-free DNA (cfDNA) has emerged as a promising biomarker in various clinical applications, particularly in cancer detection, prenatal diagnostics, and disease monitoring. Accurate classification of cfDNA sequences is crucial for improving diagnostic reliability and enabling timely clinical decisions. This study investigates the application of machine learning models—Decision...
Artificial intelligence (AI), particularly deep learning (DL), has significantly advanced medical image analysis, including the detection and classification of blood cancer through blood smear images. This review explores the state-of-the-art data mining (DM) and DL techniques applied in the identification and classification of white blood cells (WBCs), with a focus on leukemia...
This study explores the escalating cybersecurity challenges in the banking sector and the potential of large language models (LLMs) to enhance digital defense mechanisms. Employing a qualitative methodology that includes a systematic literature review, expert interviews, and case study evaluations, the research investigates the integration of LLMs in cybersecurity operations such...
This review investigates the integration of Artificial Intelligence (AI) in pharmaceutical product development, focusing on its applications in drug discovery, design, manufacturing, and quality control. Key AI methodologies, such as machine learning (ML) and deep learning (DL), are analyzed for their contributions to critical stages, including target identification, molecular...
The increasing prevalence of Artificial Intelligence (AI) across various industries necessitates an assessment of its impact on achieving the Sustainable Development Goals (SDGs). Studies indicate that AI has the potential to support 134 targets across all goals through professional, consensus-based data collection strategies. However, it may also hinder progress toward 59...
Higher education institutions operate under strict regulations and standards to ensure compliance with data protection rules, safeguard sensitive information, and preserve the privacy of employees and students. This study evaluates the expertise of staff and students at the Federal College of Education, Gidan Madi, in employing software design tools to enhance security. Using a...
Penelitian ini mengevaluasi kinerja Expert Advisor (EA) berbasis indikator Donchian Channel pada sepuluh pasangan mata uang dengan volume perdagangan tertinggi melalui metode backtesting. Pengujian dilakukan menggunakan data historis dari 1 Desember 2021 hingga 1 Desember 2024 pada platform MetaTrader 5 dengan model "Every Tick." Parameter yang digunakan meliputi stop loss 50...
Rumah Kreatif Toba merupakan platform digital yang diakses melalui situs resmi https://kreatif.tobakab.go.id dan dirancang untuk mendukung pengelolaan serta pemasaran produk Usaha Mikro, Kecil, dan Menengah (UMKM) di Kabupaten Toba. Penelitian ini bertujuan untuk mengevaluasi efektivitas penerapan tool-assisted review menggunakan SonarQube dalam pengembangan aplikasi tersebut...
Artificial Intelligence (AI) is revolutionizing healthcare by providing innovative solutions for diagnosis, treatment, and patient care. This systematic review examines recent advancements in AI-driven technologies, focusing on their applications in clinical decision support, operational optimization, and precision medicine. Findings highlight significant improvements in...
In today’s rapidly evolving technological landscape, decision-making processes within organizations are increasingly relying on advanced computational methods to enhance efficiency and accuracy. This is particularly relevant in human resource management, where selecting suitable candidates for key positions is critical. Traditional methods of staff recruitment often rely on...
At present, predictions concerning sales are predominantly based on historical sales data, a practice that frequently yields inaccurate results. Such inaccuracies can lead to substantial financial losses, compelling organizations to lower the capital expenditures associated with certain products to offset these losses. This issue primarily arises from the failure to employ an...
This paper examined the digital dynamics of three significant social justice movements: Black Lives Matter (2020), South African unrest (2021), and Mahsa Amini protests (2022) through the lens of Google Trends analysis. By tracking search interest patterns during key events, the study explored how each movement gained momentum and sustained visibility online. The analysis...