Model Jaringan Syaraf Tiruan Dalam Pengenalan Penyakit Asam Lambung

Penulis

  • Harbinder Singh,
  • Budiman,
  • Munika Murlia Giawa,
  • Nia Zulfa Yanthi Simbolon,

DOI:

https://doi.org/10.34013/saintek.v2i1.61

Abstrak

The stomach has a very important role in the process of digestion of food, therefore we need to maintain its health in order
to avoid disturbances and its function can run normally. Acid reflux or what is known as GERD is one of the diseases commonly
suffered by many people, an unhealthy lifestyle is one of the triggers for the appearance of these symptoms. GERD is a pathological
condition resulting from reflux of gastric contents into the esophagus with various symptoms that arise due to esophageal
involvement. Gastric disease is a common disease, with a prevalence of more than 50%. Neural Network (NN) is an accurate method
in helping doctors to analyze, model and understand complex clinical data in various medical fields, in research it is applied to the
introduction of gastric acid by applying the Nguyen Widrow algorithm to optimize training time in back-propagation network
architecture. . Based on the test results on the dataset, the Nguyen Widrow algorithm can only recognize 60% of the patient dataset
sample with an average time of 0.049 seconds.

Unduhan

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Diterbitkan

2019-03-29

Cara Mengutip

Harbinder Singh, Budiman, Munika Murlia Giawa, & Nia Zulfa Yanthi Simbolon. (2019). Model Jaringan Syaraf Tiruan Dalam Pengenalan Penyakit Asam Lambung. Jurnal Sains Dan Teknologi, 2(1), 39-42. https://doi.org/10.34013/saintek.v2i1.61