Prediction of Infant Mortality Using The Decision Tree and Genetic Algorithm Methods

Authors

  • Suhardjono Suhardjono Universitas Bina Sarana Informatika
  • Adjat Sudradjat Universitas Bina Sarana Informatika
  • Bilal Abdul Wahid Universitas Bina Sarana Informatika
  • Hari Sugiarto Universitas Bina Sarana Informatika
  • Hafis Nurdin Universitas Nusa Mandiri

DOI:

https://doi.org/10.31294/p.v25i1.1819

Keywords:

Decision Tree, Infant Mortality, Genetic Algorithm

Abstract

One of the things that plays a role in reducing infant mortality is the government. Based on infant mortality data in Jakarta in 2018 that has been previously tested with the decision tree algorithm, the update in this study is to use the genetic algorithm. The purpose of the update is to increase the accuracy of the results to be maximized. From the test results with the DT algorithm optimized by GA, the maximum accuracy value is 100%, and each attribute has a weight value of 1 where the value is the maximum value. After obtaining maximum results, the data will be used to reduce infant mortality, especially in Jakarta

Author Biographies

Suhardjono Suhardjono, Universitas Bina Sarana Informatika

 

 

 

Adjat Sudradjat, Universitas Bina Sarana Informatika

 

 

Bilal Abdul Wahid, Universitas Bina Sarana Informatika

 

 

Hari Sugiarto, Universitas Bina Sarana Informatika

 

 

Hafis Nurdin, Universitas Nusa Mandiri

 

 

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Published

2023-03-30

How to Cite

Suhardjono, S., Sudradjat, A., Wahid, B. A., Sugiarto, H., & Nurdin, H. (2023). Prediction of Infant Mortality Using The Decision Tree and Genetic Algorithm Methods. Paradigma, 25(1). https://doi.org/10.31294/p.v25i1.1819

Issue

Vol. 25 No. 1 (2023): March 2023 Period

Section

Articles

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Copyright (c) 2023 Suhardjono, Adjat Sudradjat, Bilal Abdul Wahid, Hari Sugiarto, Hafis Nurdin

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