Rendy, . (2022) IMPLEMENTASI ALGORITMA K-NEAREST NEIGHBOR UNTUK PREDIKSI PASIEN GAGAL JANTUNG. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
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.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No. Panggil: 1810512085] [Pembimbing 1: Ermatita] [Pembimbing 2: Ika Nurlaili] [Penguji 1: Ati Zaidiah] [Penguji 2: Sarika] |
| Uncontrolled Keywords: | Data Mining, classification, K-Nearest Neighbor, heart failure. |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > T Technology (General) |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Sistem Informasi (S1) |
| Depositing User: | Rendy - |
| Date Deposited: | 03 Feb 2023 02:48 |
| Last Modified: | 03 Feb 2023 02:48 |
| URI: | http://repository.upnvj.ac.id/id/eprint/22352 |
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