Browse Items (28 total)
- Collection: Vol 9 No 3 (2025)
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Automated Indonesian Plate Recognition: YOLOv8 Detection and TensorFlow-CNN Character Classification
The precise identification and reading of Indonesian vehicle number plates are important in many areas, including the enforcement of law, collection of charges, management of parking areas, and safety measures. This …
The Effect of Hyperparameters on Faster R-CNN inFace Recognition Systems
Facial recognition remains a significant challenge in the advancement of computer vision technologies. This research seeks todevelop a facial recognition system utilizing the Faster R-CNN architecture, with performance enhancement achieved through…
Classification of Retinoblastoma Eye Disease on Digital Fundus Images Using Geometric Features and Machine Learning
Medical image analysis is essential for detecting retinoblastoma tumors due to the ability of the method to assist doctors in examining the morphology, density, and distribution of blood vessels. The classification of normal and…
Enhancing Areca Nut Detection and Classification Using Faster R-CNN: Addressing Dataset Limitations with Haar-like Features, Integral Image, and Anchor Box Optimization
The classification and detection of areca nuts are essential for agriculture and food processing to ensure product quality and efficiency. The manual classification of areca nuts is time-consuming and prone to human error. For a more …
Automatic Classification of MultilanguageScientific Papersto the Sustainable Development Goals Using Transfer Learning
The classification of scientific papers according to their relevance to Sustainable Development Goals (SDGs) is a critical task in identifying the research development status of goals. However, with the growing volume of scientific literature…
Minangkabau Language Stemming: A New Approach with Modified Enhanced Confix Stripping
Stemming is an essential procedure in natural language processing (NLP), which involves reducing words to their root forms by eliminating affixes, including prefixes, infixes, and suffixes. The employed method assesses the efficacy of stemming, which…
Stunting Prediction Modeling in Toddlers Using a Machine Learning Approach and Model Implementation for Mobile Application
Children’s health and development are critical for maintaining national productivity and independence, with stunting being a major concern. Stunting, a form of malnutrition, impairs growth and development, affecting millions of people …
A New Framework for Dynamic Educational Marketing Segmentation in Student Recruitment: Optimizing Fuzzy C-Means with Metaheuristic Techniques
An effective educational marketing strategy requires accurate school segmentation to enhance new student recruitment. Traditional segmentation methods such as K-means are often used, but they have limitations in capturing …
Enhancing Stroke Prediction with Logistic Regression and Support Vector MachineUsing Oversampling Techniques
Stroke is a significant health concern that can result in both death and disability, making the early identification of risk factors crucial. Previous studies on stroke prediction have been limited by inadequate handling of class …
A Multi-Objective Particle Swarm OptimizationApproach for Optimizing K-Means Clustering Centroids
The K-Means algorithm is a popular unsupervised learning method used for data clustering. However, its performance heavily depends on centroid initialization and the distribution shape of the data, making it less effective for datasets with complex…