Diagnosis of Gastric Disease Based on Artificial Neural Network with Hebb Rule Algorithm

Authors

  • Victor Asido Elyakim P STIKOM Tunas Bangsa Pematangsiantar
  • Alyah Octafia STIKOM Tunas Bangsa Pematangsiantar
  • Yemima Pepayosa Sembiring STIKOM Tunas Bangsa Pematangsiantar
  • Dony Jordan Pangomoan Sirait STIKOM Tunas Bangsa Pematangsiantar
  • Angga Priandi STIKOM Tunas Bangsa Pematangsiantar

DOI:

https://doi.org/10.55123/jomlai.v4i3.6543

Keywords:

Health , Gastric Disease , Hebb Rule , Diagnosis , Artificial Neural Network

Abstract

Gastric disorders are among the most common health problems faced by society, often caused by irregular eating habits, unhealthy lifestyles, and high stress levels. The symptoms are diverse, ranging from abdominal pain and nausea to weight loss, making accurate and timely diagnosis essential to prevent more serious complications. This study aims to develop a diagnostic system for gastric diseases using Artificial Neural Networks (ANN) with the Hebb Rule algorithm, a learning principle that strengthens the connections between neurons when they are activated simultaneously. The research utilized binary-encoded data consisting of ten types of gastric diseases and twenty associated symptoms to establish patterns of correlation between symptoms and diagnoses. The results demonstrate that the system successfully recognized all test data with outcomes consistent with the expected targets, proving that the Hebb Rule is effective in mapping symptom-disease relationships even when applied to simple binary data. These findings highlight the practicality and efficiency of the Hebb Rule in building an intelligent diagnostic framework, while also showing its potential for further development with more complex datasets, such as symptom severity levels or laboratory test results. Ultimately, this research contributes to the advancement of smart medical systems that can support both healthcare professionals and the general public in performing early detection of gastric diseases quickly, accurately, and effectively.

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Published

2025-09-15

How to Cite

Victor Asido Elyakim P, Alyah Octafia, Yemima Pepayosa Sembiring, Dony Jordan Pangomoan Sirait, & Angga Priandi. (2025). Diagnosis of Gastric Disease Based on Artificial Neural Network with Hebb Rule Algorithm. JOMLAI: Journal of Machine Learning and Artificial Intelligence, 4(3), 137–148. https://doi.org/10.55123/jomlai.v4i3.6543

Issue

Vol. 4 No. 3 (2025): September 2025

Section

Articles

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Copyright (c) 2025 Victor Asido Elyakim P, Alyah Octafia, Yemima Pepayosa Sembiring, Dony Jordan Pangomoan Sirait, Angga Priandi

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