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Research ArticleOpen accessIn the keywordsHoax Classification Corona Virus (COVID-19) News in Indonesian using the Support Vector Machine (SVM) MethodWiranto Herry Utomo, Karno Juni PrayogaThe development of information technology more widely, rapidly and quickly provide convenience to the public in access information. Internet is a container or online media makes the information hasn’t been verified or proved to be true which is rapidly spreading in the community. The purpose of this study is to facilitate in determining the hoax news or facts about corona … …Journal of Computer Science, Vol. 17, Issue 8 · 13 Oct 2021 · 6,799 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAn Improved Approach for Topic Ontology Based Categorization of Blogs Using Support Vector MachineV. Subramaniyaswamy, S. Chenthur PandianProblem statement: Information search, collection and categorization from the blogosphere are still one of the important issues to be resolved. Mainly, the blogs assist the variety of interesting and useful information. Because of its increasing growth, blogs can not be categorized effectively. Therefore it is difficult to find relevant topics from the blogs. Hence blogs need to be categorized topically … …Journal of Computer Science, Vol. 8, Issue 2 · 29 Nov 2011 · 7,968 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAnalysis of Resistance to Human Immunodeficiency Virus Protease Inhibitors Using Molecular Mechanics and Machine Learning StrategiesA. Harishchander, D. Alex Anand, Sanjib SenapatiProblem statement: Drug resistance is the most important factor, which influences the failure of current HIV therapies. So, the ability to predict the drug resistance of HIV-1 protease mutants will be useful in developing more effective and longer lasting treatment regimens. Approach: Drug resistance of HIV-1 protease is predicted with two current protease inhibitors (Indinavir and Saquinavir). The problem was … …Current Research in Medicine, Vol. 1, Issue 2 · 31 Oct 2010 · 7,206 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Novel Linear-Polynomial Kernel to Construct Support Vector Machines for Speech RecognitionBalwant A. Sonkamble, D.D. DoyeProblem statement: To accept the inputs as spoken word utterances uttered by various speakers, recognize the corresponding spoken words and initiate action pertaining to that word. Approach: A novel Linear-Polynomial (LP) Kernel function was used to construct support vector machines to classify the spoken word utterances. The support vector machines were constructed using various kernel functions. The use of well … …Journal of Computer Science, Vol. 7, Issue 7 · 28 Jun 2011 · 7,013 accessesView PDFCite
Research ArticleOpen accessIn the abstractPandemic Analysis and Preparedness Using a Three Layer Machine Learning ApproachArtika Singh, Manisha JailiaOutbreak analysis provides research-based information and data to enable scientific decision-making to manage an effective response to a pandemic. Pandemic analysis has its own set of challenges, such as limited data, the need for real time analysis, and the complexity of outbreak patterns. This study proposes a hybrid approach to manage such a spread through a 3-layer machine learning-based outbreak … …Journal of Computer Science, Vol. 22, Issue 11 · 15 Oct 2026 · 632 accessesView PDFCite
Research ArticleOpen accessIn the abstractAssessing Supervised Classification Algorithms for Mangrove Detection and Differentiation from Other Forest Types in Paiton District, Probolinggo RegencyKaruniawan Puji Wicaksono, Fathor Rohman, Yasushi MitsudaRemote sensing provides an effective approach for monitoring forest cover dynamics, yet distinguishing mangroves from other forest types remains challenging in heterogeneous coastal landscapes. This study compares six supervised classification algorithms: Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Mixture Discriminant Analysis (MDA), Support Vector Machine (SVM), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) for mangrove detection in Paiton, … …OnLine Journal of Biological Sciences, Vol. 26, Issue 3 · 1 Sep 2026 · 849 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing DevOps Pipelines With Viral Spread Optimization and Hybrid Deep LearningDileepkumar S R, Juby MathewModern software teams rely on Continuous Integration and Continuous Deployment (CI/CD) pipelines to automate testing and delivery. However, these pipelines often waste resources by running unnecessary tests and failing to predict which builds will fail. This study presents a new framework that addresses three key challenges: (1) deciding which tests to run first, (2) predicting which builds will fail, and … …Journal of Computer Science, Vol. 22, Issue 6 · 3 Jul 2026 · 947 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Analysis of Fraud Detection Methods in Banking Using Machine Learning TechniquesYoussef Tounsi, Ennouri TaziFraud detection in banking requires algorithms that balance classification performance, computational efficiency, and regulatory interpretability, criteria that are rarely benchmarked together. We present a comprehensive evaluation of nine machine learning approaches (Logistic Regression, Decision Tree, Random Forest, SVM, SGD, XGBoost, CatBoost, LightGBM, and MLP) across three datasets differing in size, imbalance severity, and feature type (synthetic, real-world PCA-anonymized, and large-scale … …Journal of Computer Science, Vol. 22, Issue 6 · 22 Jun 2026 · 1,351 accessesView PDFCite
Research ArticleOpen accessIn the abstractTowards an Explainable Approach: Hybrid Residual Network and SVM for Automated Brain Tumor Detection and ClassificationKamini Lamba, Shalli RaniThe abnormal growth of brain cells leads to tumor formation, which can be fatal if not detected and treated promptly. Given the complexity of brain tumors, early detection is critical in healthcare. Traditional radiology-based tumor detection is prone to human error and delays. Hence, a computer- assisted method is needed for accurate and efficient diagnosis. With the rapid advancements in … …Journal of Computer Science, Vol. 22, Issue 1 · 11 Feb 2026 · 1,435 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimized Feature Selection for Kidney Ultrasound Image Classification Using Binary Coati Weighted Mean Vector AlgorithmFizhan Kausar, Ramamurthy B.The analysis of medical images presents many challenges, especially when making precise diagnoses. In pediatric Chronic Kidney Disease (CKD), early identification is critical because of its gradual progression to significant kidney failure. This study proposes a diagnostic framework for pediatric ultrasound image classification that incorporated machine learning and advanced feature selection methods. This approach is divided into four stages: Preprocessing, … …Journal of Computer Science, Vol. 21, Issue 12 · 22 Jan 2026 · 1,573 accessesView PDFCite