ANALISIS SURVIVAL PASIEN DIABETES MELITUS TIPE-II MENGGUNAKAN MODEL REGRESI HAZARD ADITIF LIN-YING
Survival analysis is a statistical method used to analyze data whose response variable is time an event occurs. Lin Ying Additive Hazard Regression is a method that can be used to determine the effect of the independent variable on the response variable in survival analysis. This method can be used to determine differences in risk and there is no proportionality assumption that must be met so that it can be used for certain data. The purpose of this research is to analyze the characteristics of patients, determine the probability of improving the patient's clinical condition, and determine the factors that influence the length of stay of diabetic patients at RSUD R.A. Kartini Jepara. The response variable used is the length of time the patient was hospitalized. The independent variables were age, gender, history of hypertension, history of heart disease, history of stroke, history of kidney disease, history of obesity, and history of other diseases. The analysis results from Lin Ying additive hazard regression obtained factors that influence the time to improve clinical conditions, namely history of heart disease, history of kidney disease, history of stroke, and history of other diseases.
Authors
- Triastuti Wuryandari
- Sudarno Sudarno
- Harum Tsania Salsabila
Publication Details
- Journal
- Jurnal Gaussian
- Published
- 2025-04-15
- DOI
- https://doi.org/10.14710/j.gauss.14.1.74-84
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00