Alif Faqiih, . (2024) ANALISIS PERBANDINGAN ALGORITMA RANDOM FOREST DAN XGBOOST UNTUK KLASIFIKASI PENYAKIT KARDIOVASKULAR. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
![[img]](http://repository.upnvj.ac.id/style/images/fileicons/text.png) |
Text
ABSTRAK.pdf Download (13kB) |
|
Text
AWAL.pdf Download (933kB) |
|
Text
BAB 1.pdf Restricted to Repository UPNVJ Only Download (248kB) |
|
Text
BAB 2.pdf Restricted to Repository UPNVJ Only Download (329kB) |
|
Text
BAB 3.pdf Restricted to Repository UPNVJ Only Download (209kB) |
|
Text
BAB 4.pdf Restricted to Repository UPNVJ Only Download (702kB) |
|
Text
BAB 5.pdf Download (14kB) |
|
Text
DAFTAR PUSTAKA.pdf Download (241kB) |
|
Text
RIWAYAT HIDUP.pdf Restricted to Repository UPNVJ Only Download (21kB) |
|
Text
LAMPIRAN.pdf Restricted to Repository UPNVJ Only Download (115kB) |
|
Text
HASIL PLAGIARISME.pdf Restricted to Repository staff only Download (28kB) |
|
Text
ARTIKEL KI.pdf Restricted to Repository staff only Download (422kB) |
Abstract
Heart is a muscular organ that functions as a tool to pump oxygen and blood to all organs of the body. Based on the official website of the World Health Organization (WHO), 17.9 million people die every year due to cardiovascular disease which attacks the human heart. Therefore, we need a machine learning model that has good performance and can classify cardiovascular disease quickly so that if someone is detected to be at risk of developing cardiovascular disease, they can immediately see a doctor for further examination and the disease can be treated more quickly. This research uses the Cardiovascular Disease Risk Prediction. dataset with Random Forest and XGBoost as models for classification. This research was conducted with the aim of finding the model with the best performance between Random Forest and XGBoost. The results of this study are an evaluation of Random Forest and XGBoost in classifying cardiovascular disease. The best performance was obtained from the Random Forest model with an accuracy value of 0.95, precision of 0.96, and recall of 0.93.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No.Panggil: 2010511032] [Pembimbing 1: Neny Rosmawarni] [Pembimbing 2: Musthofa Galih Pradana] [Penguji 1: Theresia Wati] [Penguji 2: Muhammad Panji Muslim] |
| Uncontrolled Keywords: | Cardiovascular Disease, Random Forest, XGBoost |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
| Depositing User: | Alif Faqiih |
| Date Deposited: | 20 Feb 2024 03:47 |
| Last Modified: | 20 Feb 2024 03:47 |
| URI: | http://repository.upnvj.ac.id/id/eprint/28385 |
Actions (login required)
 |
View Item |