IMPLEMENTASI ALGORITMA K-NEAREST NEIGHBOR UNTUK PREDIKSI PASIEN GAGAL JANTUNG
In 2019, the World Health Organization (WHO) has estimated that 17.9 million people died due to cardiovascular disease or more generally heart failure. This study aims to make a prediction of death due to heart failure. This prediction is made by making a classification with a number of criteria, na...
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2022-11-07.
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| 520 | |a In 2019, the World Health Organization (WHO) has estimated that 17.9 million people died due to cardiovascular disease or more generally heart failure. This study aims to make a prediction of death due to heart failure. This prediction is made by making a classification with a number of criteria, namely the patient's body condition and chronic diseases that the patient has and is currently suffering from. In this research, we will use the K-Nearest Neighbor algorithm in Machine Learning to carry out a classification. The data sample used was obtained from a researcher who had analyzed patient data. This dataset initially has 299 data records, which will be analyzed by dividing 20% into test data and 80% into other data. In research to make it easier to carry out the process of data analysis, the help of the Python programming language will be used to obtain a simple predictive model. The results of this study will show the level of prediction accuracy, whether it is feasible to use and then implement it into a simple website-based system. | ||
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