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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 abstractAn Integrated Disease Progression Model to Analyze Electronic Health Records With Multimodal Datasets Using Deep Learning TechniquesThulaganyo Dimakatso, Venumadhav Kuthadi, Rajalakshmi Selvaraj, Othapile DinakenyaneIn contemporary clinical environments, precisely simulating the emergence of disease is an intricate task owing to heterogeneously derived data and variability in the record of diagnoses. The research presents a stable classification model that integrates image data with formalized patient data to track patterns in disease through various stages. The suggested approach combines a multi-stage analytical methodology that includes systematic … …Journal of Computer Science, Vol. 22, Issue 2 · 19 Feb 2026 · 1,686 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
Research ArticleOpen accessIn the abstractA Novel Deep Learning Approach for Tomato Leaf Disease Detection Using Optimized CNN ArchitectureSunil K. Vithalani, Vipul K. DabhiEarly disease detection in plants is essential for sustaining agricultural yield and guaranteeing food security. A comparative analysis of transformer-based and convolutional based deep learning models for classifying tomato leaf diseases is presented. Specifically, it examines the performance of a Vision Transformer (ViT), tested both in a form of scratch training setup and through transfer learning, against well-known CNN architectures … …Journal of Computer Science, Vol. 22, Issue 1 · 7 Feb 2026 · 3,924 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Dam Safety and Management: Long Short-Term Memory Based Predictive Models for Accurate Alert ForecastingNisha C. M, N. ThangarasuDam management and early alert systems are critical for effective water resource management. Accurate prediction of dam alert signals facilitates proactive decision-making, thereby aiding in the effective management and reduction of potential risks linked to dam operations. Within this research, Long Short-Term Memory (LSTM) networks are utilized to forecast dam alert signals issued from the dam by leveraging daily parameters, … …Journal of Computer Science, Vol. 22, Issue 1 · 6 Feb 2026 · 1,632 accessesView PDFCite
Research ArticleOpen accessIn the abstractEvaluating Machine Translation for Domain Specific Low-Resource Nepali-English Language Pairs: The Impact of Tokenization on Statistical and Neural TechniquesAmit Kumar Roy, Bipul Syam PurkayasthaIn the modern era, the field of Machine Translation (MT) has seen a significant shift towards Neural Machine Translation (NMT) techniques, which have surpassed traditional Statistical Machine Translation (SMT) models in terms of the quality of translation. Despite this, the efficacy of these techniques may differ based on the language combination in consideration. While SMT is somewhat more flexible in … …Journal of Computer Science, Vol. 21, Issue 12 · 24 Jan 2026 · 1,926 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Systematic Literature Review of Software Defect Prediction Using Deep LearningAhmed Bahaa, Enas Mohamed Fathy, Ahmed Sharaf Eldin et al.The approaches associated with software defect prediction are used to reduce the time and cost of discovering software defects in source code and to improve the software quality in the organizations. There are two approaches to reveal the software defects in the source code. The first approach is concentrated on the traditional features such as lines of code, code complexity, … …Journal of Computer Science, Vol. 17, Issue 5 · 22 May 2021 · 10,973 accessesView PDFCite
Research ArticleOpen accessIn the abstractMeasuring Test Data Uniformity in Acceptance Tests for the FitNesse and Gherkin NotationsDouglas Hiura Longo, Patrícia Vilain, Lucas Pereira da SilvaThis paper presents two metrics designed to measure the data uniformity of acceptance tests in FitNesse and Gherkin notations. The objective is to measure the data uniformity of acceptance tests in order to identify projects with lots of random and meaningless data. Random data in acceptance tests hinder communication between stakeholders and increase the volume of glue code. The main … …Journal of Computer Science, Vol. 17, Issue 2 · 25 Feb 2021 · 7,577 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Experimental Study on the Embedded Software Development Approach Using TI-RTOSAloysio Augusto Rabello de Carvalho, Luiz Eduardo Galvão MartinsEmbedded systems have experienced significant growth in recent years. These systems, which power a wide range of devices from smart appliances to industrial machinery, have become integral to our daily lives and industries. However, this rapid expansion introduces new challenges for developers. A critical decision involves whether to employ a Real-Time Operating System (RTOS) or to forgo it, depending on … …Journal of Computer Science, Vol. 21, Issue 6 · 17 Jul 2025 · 3,073 accessesView PDFCite
Review ArticleOpen accessIn the abstractWeb Scraping for Product Recommendations: A Review of Techniques and ApplicationsAmarinder Kaur, Deepak PrasharA comprehensive method for developing a reliable product recommender system leveraging sophisticated web scraping technologies, machine learning, and natural language processing techniques. The proposed system addresses key challenges in personalized product recommendation, including the difficulty of integrating diverse data from multiple e-commerce platforms, ensuring data quality, and improving recommendation accuracy to enhance user experience. Specifically, this research tackles issues related … …Journal of Computer Science, Vol. 21, Issue 6 · 21 Jun 2025 · 4,234 accessesView PDFCite