IMPLEMENTASI ALGORITMA K-NEAREST NEIGHBOR UNTUK PREDIKSI PASIEN GAGAL JANTUNG - Rendy (2022)
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.