Implementation of a Machine Learning with a Python Programming Approach to Predict the Level of Disease Cases

Authors

  • Ridwan STIE Dewantara, Bogor, Indonesia
  • Prio Kustanto Universitas Bhayangkara Jakarta Raya, Jakarta, Indonesia

Keywords:

digital transformation, machine learning, classification, outbreak prediction

Abstract

Digital transformation invariably results in the development of data-driven insights. To counteract digital transformation in the health domain, tools that can perform predictive analysis are needed. The use of machine learning to predict the severity of a disease can aid in the prompt formulation of health care policies. Machine learning models employ several techniques in classification algorithms with a framework provided by the Python programming language. In this case, the used data include a dataset that was collected from the Indonesian Health Profile, which includes information on health-related behaviors, health-related laws, and sociodemographic trends. Decision tree modeling has very good accuracy when classifying the severity of illness.

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Published

2024-10-05

How to Cite

Ridwan, & Kustanto, P. (2024). Implementation of a Machine Learning with a Python Programming Approach to Predict the Level of Disease Cases. Greenation Computer and Information Review, 1(1), 15–24. Retrieved from https://greenpub.org/GCIR/article/view/673

Issue

Vol. 1 No. 1 (2024): Greenation Computer and Information Review (October 2024)

Section

Articles

License

Copyright (c) 2024 Ridwan, Prio Kustanto

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