Browse Items (12 total)
- Collection: Vol 8 No 5 (2024)
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An Investigation Towards Resampling Techniques and Classification Algorithms on CM1 NASA PROMISEDataset for Software Defect Prediction
Software defect prediction is a practical approach to improvingthequality and efficiency of software testing processes. However,establishing robust and trustworthy models for software defect prediction is quite challenging due to the…
ESP32 and MAX30100 with Chebyshev Filter for Enhanced Heart and Oxygen Measurement
Health monitoring is important in the technology and information era. A health monitoring device must possess high accuracy in monitoring an individual's health. The MAX30100 sensor still exhibits low accuracy and requires improvements to enhance its…
Prototype of SwiftletNest Moisture ContentMeasurement Using Resistance Sensor and Machine Learning
Swiftletnests are highly valued for their health and cosmetic benefits, with moisture content crucial in determining their quality. Traditional moisture measurement methods are often slow and can potentially damage the samples. This …
Designing aKnowledge-Based Chatbot to Elevate Business Licensing Services in Indonesia
The business licensing process in Indonesia often faces several challenges, including lack of information, unstable system, complicated procedure, and slow response to complain. These issues can hinder economic growth and limit access…
Quantum Perceptron:A Novel Approach to Predicting Unemployment Levels in North Sumatra Province
The application of Quantum Computing to improve the perceptron algorithm in unemployment prediction is a new aspect ofthis research. This study focuses on unemployment, which is a big challenge for the young generation in Indonesia, especially in …
Cloud Node Auto-Scaling System Automation Based on Computing Workload Prediction
Auto-scaling systems in cloud computing are important for handling application workload fluctuations. This research usesmachine learning to predict resource requirements based on workload work patterns and design an automatic scaling…
Improving Diabetes Prediction Accuracy in Indonesia: A Comparative Analysis of SVM, Logistic Regression, and Naive Bayes with SMOTE and ADASYN
This study aims to enhance the accuracy of diabetes prediction models in Indonesia by comparing the performance of Support Vector Machines (SVM), Logistic Regression, and Naïve Bayes algorithms, both with and without synthetic …
Optimizing Book Stocktaking Process: Integration of Mobile Robot QRCode Commands with SLiMS
This study presents a novel approach to enhance efficiency and precision in library management through the utilization of QR code technology. Integration of a mobile robot equipped with a QR code reader into the stocktake process, interfaced with…
Quantum-Enhanced K-Medoids Clustering: Comparative Analysis of Stroke Medical Data
Stroke is a severe medical condition that occurs when the blood supply to parts of the brain is interrupted or reduced, resulting in brain tissue that lacks oxygen and nutrients. This causes brain cells to start to die in minutes. Early prevention…
Machine Learning Methods for Forecasting Intermittent Tin Ore Production
Effective production forecasting is important for resource planning and management in the mining industry.Tin ore production from Cutter Section Dredges (CSD) may fluctuatedue to a variety of factors, in which there are periods when the production is…