Browse Items (28 total)
- Collection: Vol 9 No 3 (2025)
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Development of IoT-based Automatic Water Drainage System on Fishing Boatto Improve Operational Efficiency
The profession of fishermen requires a reliable system to remove stagnant water from fishing boats, as manual drainage is time-consuming and inefficient. This study proposes an IoT-based automatic water drainage systemwithout using an inverter or …
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 …
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 …
Prediction of Financial Distress in Retail Companies Using Long-Short Term Memory (LSTM)
Financial distress is a condition in which an entity struggles to meet its debt and operating obligations.. Financial distress can lead to bankruptcy or company closure if corrective action is not taken. This study aims to forecast financial distress…
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 …
Health Risk Classification Using XGBoost with Bayesian Hyperparameter Optimization
Health risk classification is important. However, health risk classification is challenging to address using conventional analytical techniques. The XGBoost algorithm offers many advantages over the traditional methods for …
XGBoost Algorithm for Cervical Cancer Risk Prediction: Multi-dimensional Feature Analysis
Cervical cancer continues to pose a significant global health challenge, with early detection remaining the cornerstone for effective intervention. This study is situated at the intersection of clinical oncology and computational…
Enhancing Tomato Leaf Disease DetectionviaOptimized VGG16and Transfer Learning Techniques
dentification of tomato leaf disease remains difficult because standard approaches are frequently incorrect in identifying distinct signs. Convolutional Neural Networks (CNNs) perform well in image classification and pattern…
Developmentof aDocument-Based Gait System With Interactive Visualisation forClinical Analysis
Gait analysis is a crucial aspect of biomechanics and medical rehabilitation, used to detect movement disorders, assess therapy effectiveness, and understand human walking patterns. In Indonesia, gait research remains limited, with most data sourced…
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 …