ANALISA PERFORMA ALGORITMA MACHINE LEARNING DALAM PREDIKSI PENYAKIT LIVER
| العنوان: | ANALISA PERFORMA ALGORITMA MACHINE LEARNING DALAM PREDIKSI PENYAKIT LIVER |
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| المؤلفون: | Mahdiawan Nurkholifah, null Jasmarizal, Yusran Umar, null Rahmaddeni |
| المصدر: | Jurnal Indonesia : Manajemen Informatika dan Komunikasi. 4:164-172 |
| بيانات النشر: | Lembaga KITA, 2023. |
| سنة النشر: | 2023 |
| الوصف: | Currently in the world of medicine, determining liver inflammation is something that is not easy to do. But there are medical records that have kept the patient's symptoms and diagnosis of liver inflammation. The weaknesses of the manual method encourage researchers to develop a method that does not depend 100% on humans. The developed method utilizes a computer as a tool to analyze data. This kind of thing is certainly very useful for health experts. They can use existing medical records as an aid in making decisions about the diagnosis of a patient's disease. In this study, we analyzed the performance of machine learning algorithms by comparing the support vector machine, naïve Bayes and k-nearest neighbor algorithms. This study aims to determine the performance of which algorithm has the highest accuracy in liver disease data. From the research results using splinting data 80:20 it can be concluded that the Naïve Bayes algorithm model has better performance than other algorithm models when using the SMOTE technique with an accuracy value of 65.51%, whereas when not using the SMOTE technique the Support Vector Machine algorithm has the highest performance. better than other algorithm models with an accuracy value on the data not 72.41%. |
| تدمد: | 2723-7079 2776-8074 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::5f8a35d51c1703c3c34feb85014eefda https://doi.org/10.35870/jimik.v4i1.149 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi...........5f8a35d51c1703c3c34feb85014eefda |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 27237079 27768074 |
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