Sistem diagnosa penyakit liver menggunakan Metode Artificial Neural Network: Studi berdasarkan Dataset Indian Liver Patient Dataset

Alviola, Nuril Afni, Fathurrahman, Zaky, Rifai, Rokhim Nur and Afrah, Ashri Shabrina (2023) Sistem diagnosa penyakit liver menggunakan Metode Artificial Neural Network: Studi berdasarkan Dataset Indian Liver Patient Dataset. Jurnal Informatika: Jurnal Pengembangan IT, 8 (3). pp. 308-312. ISSN 2548-9356

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Abstract

Abstract In humans, a condition known as liver disease attacks the organ's ability to regulate the body's levels of fat or cholesterol. The effects of liver illness vary according to their severity and how well they respond to treatment. Therefore, the development of a liver disease prediction system is pertinent and helpful in enabling medical professionals to act appropriately more immediately. The Artificial Neural Network (ANN) approach can be used to create this system. The aim of the classification is to reveal the accuracy of the ANN in classify the liver disease dataset. The dataset is divided into 3 steps using this method: data pretreatment, data processing, and data analysis. In order to create a new dataset, data preprocessing is done by separating and mending the original dataset. The determination of the hidden layer, the activation model, and the normalization of the model are carried out during data processing. There are accuracy values, error values, confusion matrices, and classification reports in the last stage, which is dataset evaluation. This model predicts a true negative score of 70, a true positive score of 14, a false negative score of 16, and a false positive score of 17. This model successfully classified datasets with an accuracy of 71.79%, showing that it is effective.

Item Type:	Journal Article
Keywords:	ANN; machine learning; knowledge engineering; liver
Subjects:	08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080105 Expert Systems
Divisions:	Faculty of Technology > Department of Informatics Engineering
Depositing User:	Ashri Shabrina Afrah
Date Deposited:	29 Dec 2023 09:18

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