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- W4323520569 abstract "Diabetes Mellitus is a metabolic disease of several etiologies characterized by chronic hyperglycemia with impaired carbohydrate, fat, and protein metabolism due to defects in insulin secretion, insulin action, or both. Diabetes will make approximately 6.7 million deaths in 2021, so one person dies every 5 seconds. Diabetes accounts for at least USD 966 billion dollars in health spending and has seen a 316% increase over the last 15 years. In Indonesia, Diabetes Mellitus will reach 21 million people in 2030 and is increasing. In the long term, it will place a significant financial burden on the health care system as well as on individuals and society as a whole. Based on the description above, the purpose of this study is to predict people with Diabetes Mellitus using the K-Nearest Neighbor (K-NN) algorithm. The data is taken from Kaggle and data processing uses Python. The testing model in this study used a confusion matrix and the testing accuracy used Recall and precision. The results show that K-NN has an accuracy value of 84.41%, which means for every 77 test samples there are 17 people diagnosed as positive. This is indicated by the recall value of 92.85% and the precision value of 86%. This result shows the K-NN algorithm has good accuracy in the prediction problem." @default.
- W4323520569 created "2023-03-09" @default.
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- W4323520569 date "2022-12-08" @default.
- W4323520569 modified "2023-09-27" @default.
- W4323520569 title "Prediction Analysis of Diabetes Mellitus Based on Machine Learning Algorithm" @default.
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- W4323520569 doi "https://doi.org/10.1109/isriti56927.2022.10052794" @default.
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