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130 articles for “Predictor”
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Research ArticleOpen accessIn the abstractComputational Prediction of Diabetic Nephropathy-Associated Comorbidities and Their Key Genes by Analyzing RNA-Seq DataChaity Paul, Md. Ashiq Uddin, Rupa Dey et al.Diabetic Nephropathy (DN) is a complex health condition that leads to various kidney diseases. According to the World Health Organization, over 2 million deaths have been reported due to diabetes and diabetes related kidney diseases in 2021. And at the recent 78th World Health Assembly, chronic kidney disease was reported to be one of the most common diabetes-related complications, and … …OnLine Journal of Biological Sciences, Vol. 26, Issue 2 · 19 May 2026 · 1,667 accessesView PDFCite
Research ArticleOpen accessIn the abstractExploring University Students' Perceptions of AI Tools in Programming Education: An Extended TAM ApproachAreej Abdullah AlfuhaidGenerative Artificial Intelligence (AI) is commonly used in programming education. Tools such as ChatGPT and GitHub Copilot aid in code generation, debugging, and explanation. The benefits are clear, though concerns about learning quality and academic integrity persist.We tested an extended Technology Acceptance Model (TAM) for university programming courses. The model included perceived usefulness and perceived ease of use. It added … …Journal of Computer Science, Vol. 22, Issue 3 · 11 Mar 2026 · 2,061 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Quantitative Analysis of Preparedness and Performance: Predictive Indicators in First-Year Tertiary MathematicsGurudeo Anand TularamStudent preparedness at university entry plays a critical role in determining success in mathematics courses. This study investigates how three observable behaviours: (1) completion of weekly problem sets, (2) regular tutorial attendance, and (3) performance on a mid-semester test. We investigate how they relate to each other and their final examination results. Over five years, data were collected from 450 … …Journal of Social Sciences, Vol. 21, Issue 1 · 10 Oct 2025 · 2,724 accessesView PDFCite
Research ArticleOpen accessIn the abstractMachine Learning Oceanographic Data for Prediction of the Potential of Marine ResourcesDenny Arbahri, Oky Dwi Nurhayati, Imam MuditaMarine data and information are very important for human survival, therefore this data and information is attractive to investors because of the potential economic value. This data and information has been difficult to obtain, the solution to overcome this is by analyzing oceanographic data for 2009-2019 collected from the marine database belonging to the Agency for the Study and Application … …Journal of Computer Science, Vol. 20, Issue 2 · 8 Jan 2024 · 5,970 accessesView PDFCite
Research ArticleOpen accessIn the abstractDecision Support Model for Employee Selection Based on Data Mining and Fuzzy LogicClarissa Elfira Amos Pah, Ditdit Nugeraha UtamaThis paper explains the use of data mining and fuzzy logic in optimizing decision making for employee recruitment, especially in IT Consultant company. This method addresses the company's need to recruit employees with more objective and accurate by utilizing historical data to find patterns of potential employees for the company. First, classification will be carried out using data mining to … …Journal of Computer Science, Vol. 16, Issue 5 · 4 Jun 2020 · 7,667 accessesView PDFCite
Research ArticleOpen accessIn the abstractBayesian Network Inference in Binary Logistic Regression: A Case Study of Salmonella sp Bacterial Contamination on Vannamei ShrimpPratnya Paramitha Oktaviana, Kartika FithriasariRecently binary logistic regression has been used to identify four factors or predictor variables that supposedly influence the response variable, which is testing result of Salmonella sp bacterial contamination on vannamei shrimp. Binary logistic regression analysis results that there are two predictor variables which is significantly affect the testing result of Salmonella sp bacterial contamination on vannamei shrimp, those are … …Journal of Mathematics and Statistics, Vol. 13, Issue 4 · 22 Dec 2017 · 7,667 accessesView PDFCite
Research ArticleOpen accessIn the abstractUnivariate Generalized Additive Models for Simulated Stationary and Non-Stationary Generalized Pareto DistributionMostafa Behzadi, Mohd Bakri Adam, Anwar FitriantoGeneralized additive models as a predictor in regression approaches, are made up over cubic spline basis and penalized regression splines. Despite of linear predictor in GLM, generalized additive models use a sum of smooth functions of covariates as a predictor. The data which are used in this study have generalized Pareto distribution and have been simulated by inversion method. The … …Journal of Mathematics and Statistics, Vol. 13, Issue 2 · 3 Jun 2017 · 7,430 accessesView PDFCite
Research ArticleOpen accessIn the abstractModel Comparison for the Prediction of Stock Prices in the NYSEVictoria Switlyk, Junfeng ShangThe stock market is an integral part of investments as well as the economy. The prediction of stock prices is an exciting and challenging problem that has been considered by many due to the complexity and noise within the market and to the potential profit that can be yielded from accurate predictions. We aim to construct and compare models used … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 26 Sep 2019 · 7,475 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdolescent Internal Environmental Locus of Control Scale (AINELOC) Measurement ToolCarnell Colebrook-ClaudeThis study aims to validate the Adolescent Internal Environmental Locus of Control (AINELOC) scales (green consumer, activist, advocate and recycling attitude). The AINELOC was used to identify the association between internal locus of control and pro-environmental behaviors in adolescents. The study was conducted because of the lack of data in the literature about the subject matter and developed based on … …American Journal of Environmental Sciences, Vol. 15, Issue 2 · 29 Apr 2019 · 8,608 accessesView PDFCite
Research ArticleOpen accessIn the abstractApplications of Machine Learning in Building Energy Prediction and SavingsPriyan Rai, Dr. Nabil Nassif, Kevin Eaton, Alexander RodriguesIn a constantly advancing world with growing needs, buildings play in important role in the daily functioning of the society. Developing more and more advanced techniques to optimize the working of these buildings is highly important for a constant growth. Modern computational techniques have opened doors to create advanced models that can utilize efficient techniques to produce highly accurate results. … …Energy Research Journal, Vol. 10, Issue 1 · 15 Mar 2019 · 8,038 accessesView PDFCite