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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 "96-102" : 1 Documents clear
POHON KEPUTUSAN DENGAN ALGORITMA C.45 UNTUK PENENTUAN TINGKAT RESIKO PENYAKIT GERD Puspitorini, Sukma; Wahyuning Astuti, Reny; Rivatunisa, Cyntia
JURNAL AKADEMIKA 96-102
Publisher : LP2M Universitas Nurdin Hamzah

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Abstract

Gastroesophageal Reflux Disease (GERD) is a disorder in which the contents of the stomach reflux repeatedly into the esophagus (esophagus), which causes symptoms and or complications that, interfere. The purpose of this study was to determine the level of risk of GERD in respondents based on diet, lifestyle, and perceived symptoms. The method used in this study is a decision tree with the C.45 algorithm. To make a decision tree WEKA tools are used, where data obtained from the results of a questionnaire distributed to 51 respondents to determine diet and lifestyle, then to predict the risk level of GERD a web-based decision support system was built using the Php programming language and the MySQL database. The input needs consist of respondent data input, questionnaire question data input, news data input, and training data input, with process requirements that include respondent data processing, questionnaire question data processing, news data processing, questionnaire data processing, and reporting process, which will produce training data output reports by gender, training data reports by date and prediction results. This study resulted in a design of a decision support system to determine the risk level of GERD that can help medical staff aware and educate the public to recognize early symptoms of GERD disease and to help general practitioners advise patients with GERD.

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