Implementation of a Web-Based Diabetes Mellitus Prediction Information System
Keywords:
Diabetes Mellitus, Diabetes prediction, Stacking method, C4.5 algorithm, Support Vector Machine (SVM)Abstract
Design and development of a web-based diabetes prediction system utilizing a stacking method that combines the C4.5 algorithm and Support Vector Machine (SVM). Testing results indicate that the developed prediction model achieves an accuracy of 80%, with 8 out of 10 predictions matching the actual patient conditions, using a dataset from the national institute of diabetes and digestive and kidney diseases. After testing, the system was deployed and is accessible to users anytime and anywhere. Website access testing using Wireshark confirmed that data communication, including login information and prediction results, is securely encrypted. In addition to serving as a prediction tool, this system is equipped with additional features such as health tools, expert advice, and guidelines for diet and exercise, aiding users in managing their overall health.
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Copyright (c) 2024 Hillara Isfalana June, Vera Veronica, A. Abd. Jabbar (Author)
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