REKAYASA PERANGKAT LUNAK DETEKSI DINI KECENDERUNGAN GANGGUAN KESEHATAN MASYARAKAT TERTINGGAL DAN PESISIR DENGAN BAYESIAN NETWORK

Authors

  • Ilham Ilham Universitas Muhammadiyah Gresik Jl.Sumatra 101 GKB Gresik

:

https://doi.org/10.9744/informatika.13.2.39-43

Keywords:

Model, Bayessian Network, coastal, Hybrid algorithm

Abstract

This study was conducted to see the trend of diseases caused by unhealthy lifestyles on disadvantaged communities and coastal villages around Gresik and Tuban using hybrid algorithms through the construction of the structure of Bayesian Network. The problem to be solved in this study is no system that can detect a relationship between unhealthy behavior that caused the disease. Model of this structure has never been applied directly in the field to detect a causal events for example, if a behavior is unhealthy will arise disease. Application of this model needs to be done with a field study to determine and prove the actual benefits of the concept of a hybrid construction of Bayesian network structure. The purpose of this research is to produce a software model capable of early detection of disease risk propensity underdeveloped rural and coastal communities who have unhealthy lifestyles in the form of construction of the structure and generates a probability value with a tendency disease. The comparison between the structure of the origin of the structure of the trial results indicate the level of suitability for complete test data difference of 10% to the original structure, and suitability for the test data is incomplete for more than 20% depending on the amount of his missing value. The validity of that smoke will have the tendency has tuberculosis disease, bronchitis or Lung Cancer through the test system is 80% to 90%.

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Published

2016-02-01

How to Cite

Ilham, I. (2016). REKAYASA PERANGKAT LUNAK DETEKSI DINI KECENDERUNGAN GANGGUAN KESEHATAN MASYARAKAT TERTINGGAL DAN PESISIR DENGAN BAYESIAN NETWORK. Jurnal Informatika, 13(2), 39-43. https://doi.org/10.9744/informatika.13.2.39-43

Issue

Vol. 13 No. 2 (2015): NOVEMBER 2015

Section

Articles

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