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Akademika
Published by Universitas Nurdin Hamzah
ISSN : 19073984     EISSN : 25411760     DOI : https://doi.org/10.53564
Core Subject : Science,
Computer Science & IT
Jurnal Akademika merupakan media publikasi hasil penelitian dari para akademisi serta praktisi yang berkenaan dengan teknologi informasi dengan beberapa topik bahasan meliputi sistem informasi, jaringan komputer, keamanan sistem, multimedia, kecerdasan buatan, dan sistem pakar. Jurnal Akademika dikelola dibawah Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Nurdin Hamzah yang rutin terbit 2 kali setahun pada bulan april dan november.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 1 Documents
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Search results for , issue "28-34" : 1 Documents clear
RANCANG BANGUN APLIKASI PENENTUAN TINGKAT RISIKO PENYAKIT GASTROESOFAGEAL REFLUX DISEASE (GERD) BERDASARKAN POLA MAKAN, GAYA HIDUP, DAN STATUS GIZI DENGAN POHON KEPUTUSAN KONSEP ENTROPY Hambali Furnawan; Sukma Puspitorini
JURNAL AKADEMIKA 28-34
Publisher : LP2M Universitas Nurdin Hamzah Jambi

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Abstract

Gastroesophageal Reflux Disease (GERD) is a gastrointestinal disease in which oesophageal abnormalities that cause gastric fluid to flow back (reflux) into the esophagus and cause heartburn symptoms typical of burning in the chest, sometimes accompanied by pain. GERD can be experienced by any person at any time and in intensity which often can cause the inflammation of the esophagus esofagistis (esophagus) which can lead to complications such as esophageal stricture, Barrett's esophagus, and esophageal cancer. Lifestyle factors and good eating habits can be the cause of GERD. This GERD disease risk level determination aplication programme design is made to determine the extent of a person's risk of experiencing GERD seen lifestyle factors, diet, and nutritional status as well. Data obtained from questionnaires given to patient. The average point on each variable for lifestyle factors and diet then categorized. While the nutritional status is obtained by finding a body mass index (BMI) of the patient. Of the categories obtained on each factor, the classification rule set (classification rule) which will then be represented in the form of a decision tree (decision tree). The results obtained from a search result is a tree-level person's risk of disease GERD.

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