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164 articles for “data integration”
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Review ArticleOpen accessIn the abstractEconomic Theory and Machine Learning Integration in Asset Pricing and Portfolio Optimization: A Bibliometric Analysis and Conceptual FrameworkPatrick Kevin Aritonang, Sudarso Kaderi Wiryono, Taufik FaturohmanThe integration of Machine Learning (ML) with economic theory has transformed financial market analysis, particularly in asset pricing and portfolio optimization. This study synthesizes existing research, identifies gaps and elucidates ML's impact on enhancing economic models and strategies through a Systematic Literature Review (SLR) of 401 relevant documents using bibliometric methodology and VOS viewer. Results show an increasing trend in … …Journal of Computer Science, Vol. 20, Issue 10 · 7 Aug 2024 · 5,725 accessesView PDFCite
Research ArticleOpen accessIn the abstractDesign of Enterprise Architecture Using Zachman Framework at Private School in Center JakartaKeysia Aprilia, Francka Sakti Lee, Yemima Monica Geasela et al.Technology is currently fundamental and necessary, including in the education sector, where information technology, such as enterprise architecture, can be applied to support and facilitate school business processes. Private schools in Central Jakarta are one of the schools that utilize information technology in running their business. However, currently, schools still need to use information technology optimally, so it is necessary … …Journal of Computer Science, Vol. 20, Issue 9 · 8 Jul 2024 · 6,364 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Adaptive Data Preprocessing Framework for Improved Learning: A Case Study of Tangier Container TerminalMostafa Al Uahabi, Hicham Attariuas, Mohammed Saleh, Mohamed ChentoufContainer terminals are critical nodes within the maritime transportation system that have a vital function in global merchandise trade, handling a significant volume of cargo through the use of various equipment and personnel. Thus, the efficiency of container terminal operations relies heavily on the ability to collect, analyze, and utilize operational data. However, such data can be corrupted by noise, … …Journal of Computer Science, Vol. 20, Issue 3 · 25 Jan 2024 · 5,593 accessesView PDFCite
Research ArticleOpen accessIn the abstractMachine Learning Approaches for the Prediction of Gas Turbine TransientsArnaud Nguembang Fadja, Giuseppe Cota, Francesco Bertasi et al.Gas Turbine (GT) emergency shutdowns can lead to energy production interruption and may also reduce the lifespan of a turbine. In order to remain competitive in the market, it is necessary to improve the reliability and availability of GTs by developing predictive maintenance systems that are able to predict future conditions of GTs within a certain time. Predicting such situations … …Journal of Computer Science, Vol. 20, Issue 5 · 28 Feb 2024 · 7,673 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Data-Sharing Model to Secure Borders Using an Artificial-Intelligence-Based Risk Engine and Big-Data ConceptsMohammad S. Al Rousan, Benedetto IntrigilaThe primary aim of this research is to develop a framework for data management and sharing that will enable countries to share complex data about known and unknown high-risk passengers to streamline border-control security processes through the use of big data analytics and Artificial Intelligence (AI). A total of 15 semi-structured interviews were used to gather qualitative data. A thematic … …American Journal of Applied Sciences, Vol. 19, Issue 1 · 2 May 2022 · 6,942 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntegrating (OLAP) Online Analytical Processing With a Fast Algorithm for Epileptic Seizures DetectionIlyas Zidane, Wajih Rhalem, Nordine ZidaneEpilepsy is a neurological disorder characterized by recurrent seizures, significantly impacting the quality of life of patients. Effective detection and analysis of epileptic seizures are crucial for timely intervention and management. This paper presents the integration of a fast algorithm for epileptic seizures detection with an OLAP (Online Analytical Processing) system using a star schema data warehouse model. By leveraging … …Journal of Computer Science, Vol. 22, Issue 10 · 12 Oct 2026 · 694 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Active Learning Ensemble Framework for Tropical Crop Yield PredictionAmol Bhilare, Debabrata Swain, Megh Patel et al.Agriculture always has great importance among all different sectors, not only in the world but also in India. It has a significant impact on food security and largely controls the economy. At present, technological advancements have significantly enhanced agricultural productivity, but it can still be further improved by the integration of new cutting-edge techniques like Artificial intelligence. Among the factors … …Journal of Computer Science, Vol. 22, Issue 9 · 11 Sep 2026 · 829 accessesView PDFCite
Research ArticleOpen accessIn the abstractBlockchain-Enabled Privacy-Preserving Access Control for Electronic Health Records Using Smart ContractsG. Bhanu Prasad, M. Venkateswara RaoElectronic medical records are crucial for providing high-quality healthcare, but they also raise serious privacy and security issues. Traditional centralised storage systems are vulnerable to manipulation, hacking, and illegal access. This study suggests a smart contract-based blockchain architecture that provides decentralised, unaltered, and privacy-preserving access control for EMRs. The model integrates cryptographic techniques like AES-256 encryption and SHA-256 hashing for … …Journal of Computer Science, Vol. 22, Issue 6 · 22 Jun 2026 · 1,313 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Comparative Study of Resampling, Cost-Sensitive, and Ensemble Techniques for Handling Class Imbalance in Indonesian Financial DataGunawan Kurnia, Ditdit Nugeraha UtamaHandling class imbalance is a critical challenge in machine learning applications, particularly in financial domains where minority instances often represent significant anomalies such as fraud or audit risks. Various oversampling and undersampling methods were tested, alongside cost-sensitive adjustments and ensemble models including Random Forest, AdaBoost, Gradient Boosting, and XGBoost. The evaluation, based on 10-fold stratified cross-validation and performance metrics such … …Journal of Computer Science, Vol. 22, Issue 2 · 27 Feb 2026 · 1,882 accessesView PDFCite
Research ArticleOpen accessIn the abstractSystematic Literature Review of Graph Neural Networks in Disaster Management: Methods, Applications, and Future DirectionsSularno, Wendi Boy, Putri Anggraini et al.The increasing frequency and complexity of natural disasters underscore the urgent need for intelligent systems that support timely and effective decision-making. Graph Neural Networks (GNNs) have emerged as a powerful deep-learning paradigm for modeling spatial and relational data, offering distinct advantages for disaster management. This study presents a Systematic Literature Review (SLR) of GNN-based approaches for disaster mitigation, emergency response, … …Journal of Computer Science, Vol. 22, Issue 2 · 17 Feb 2026 · 2,043 accessesView PDFCite