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All Journal Panrita Abdi - Jurnal Pengabdian pada Masyarakat Sinkron : Jurnal dan Penelitian Teknik Informatika Tech-E JRST (Jurnal Riset Sains dan Teknologi) Jurnal Media Elektro : Journal of Electrical Power, Informatics, Telecommunication, Electronics, Computer and Control System Journal of Informatics and Communication Technology (JICT)
Arif Rahman Hakim
Universitas Medika Suherman
Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Mathematics Other

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Journal : Journal of Informatics and Communication Technology (JICT)

 1 
Prediction of Liver Disease Using a Linear Regression Algorithm Deny Haryadi; Dewi Marini Umi Atmaja; Arif Rahman Hakim
Journal of Informatics and Communication Technology (JICT) Vol 5 No 1
Publisher : PPM Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52661/j_ict.v5i1.182

Abstract

The liver is the most essential organ in the human body. Hepatitis is one such disorder affecting the liver and is a global health issue, including in Indonesia. Liver disease is an inflammatory condition of the liver that can be triggered by genetic factors, viral infections, alcohol consumption, and the use of certain drugs. In principle, prevention of hepatitis or liver disease can be done by adopting a healthy lifestyle. In addition, early detection is also very important in preventing death in those affected by this disease. One method for early detection is through the application of data mining, which can help predict and reduce mortality in patients affected by this disease. Linear regression is a data mining technique utilized to predict the dependent variable or outcome based on the independent variable or predictor. The study conducted tests on this algorithm and obtained a Root Mean Squared Error of 0.349 +/- 0.000. This indicates the presence of a correlation or functional relationship (cause and effect) between the dependent variable (criterion) and the independent variable (predictor). The purpose of this testing process is to detect liver disease using the linear regression algorithm.
Co-Authors Amat Basri Amat Basri Amat Basri Andri Ariyanto Deny Haryadi Dewi Marini Umi Atmaja Dewi Marini Umi Atmaja Dewi Marini Umi Atmaja Muhamad Syafii Risma Adisty Nilasari Tugiman Tugiman