ANALISIS KETAHANAN HIDUP PASIEN DIABETES MELITUS DENGAN METODE REGRESI COX PROPORTIONAL HAZARD PADA DATA SATU PARAMETER TERSENSOR TIPE II

Diabetes mellitus (DM) is a chronic metabolic disease or disorder with various causes characterized by high blood sugar levels accompanied by impaired metabolism of carbohydrates, fats, and proteins as a result of impaired insulin function. However, in diabetics, the pancreas is unable to produce insulin as the body needs. Without insulin, the body's cells cannot absorb and process glucose into energy. Although this disease is not contagious, the impact it has on health is crucial. Seeing this, researchers want to see the magnitude of the combination of factors that affect the survival of people with diabetes mellitus using the cox proportional hazard regression method. To find out this, a case study of diabetes mellitus data at PKU Muhammadiyah Hospital Yogyakarta was used. The data analysis stage uses exponentially distributed data of one type II sensor parameter and uses the cox regresion proportional hazard method. The results of the application of the two methods to the survival data of patients with type2 diabetes mellitus inpatient survival time at a significance level of 5% that the independent variables used, together affect patients affected by diabetes mellitus until death as many as 6 cases or 18.2% of 33 data cases. With the chance of hospitalization time in the next 9 days is 0.78267 and in the next 15 days is 0.66470.

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Journal
Jurnal Eksbar
Published
2025-06-20
DOI
https://doi.org/10.29408/eksbar.v2i1.29126
Primary Topic
Artificial Intelligence in Healthcare
Type
article
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article

ANALISIS KETAHANAN HIDUP PASIEN DIABETES MELITUS DENGAN METODE REGRESI COX PROPORTIONAL HAZARD PADA DATA SATU PARAMETER TERSENSOR TIPE II

Zulfa Bariyyah, Bq. Yulia Setia Silviani, Alissa Chintyana, Liska Lisnawati Liska lisnawati
Jurnal Eksbar
Artificial Intelligence in Healthcare
article

ANALISIS KETAHANAN HIDUP PASIEN DIABETES MELITUS DENGAN METODE REGRESI COX PROPORTIONAL HAZARD PADA DATA SATU PARAMETER TERSENSOR TIPE II

Zulfa Bariyyah, Bq. Yulia Setia Silviani, Alissa Chintyana, Liska Lisnawati Liska lisnawati
article en

Abstract

Diabetes mellitus (DM) is a chronic metabolic disease or disorder with various causes characterized by high blood sugar levels accompanied by impaired metabolism of carbohydrates, fats, and proteins as a result of impaired insulin function. However, in diabetics, the pancreas is unable to produce insulin as the body needs. Without insulin, the body's cells cannot absorb and process glucose into energy. Although this disease is not contagious, the impact it has on health is crucial. Seeing this, researchers want to see the magnitude of the combination of factors that affect the survival of people with diabetes mellitus using the cox proportional hazard regression method. To find out this, a case study of diabetes mellitus data at PKU Muhammadiyah Hospital Yogyakarta was used. The data analysis stage uses exponentially distributed data of one type II sensor parameter and uses the cox regresion proportional hazard method. The results of the application of the two methods to the survival data of patients with type2 diabetes mellitus inpatient survival time at a significance level of 5% that the independent variables used, together affect patients affected by diabetes mellitus until death as many as 6 cases or 18.2% of 33 data cases. With the chance of hospitalization time in the next 9 days is 0.78267 and in the next 15 days is 0.66470.

Jurnal EksbarVol. 2(1)
Universitas Amir Hamzah (ID)
Good health and well-being
Openalex Percentile: Top 83%
Artificial Intelligence in Healthcare
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ANALISIS KETAHANAN HIDUP PASIEN DIABETES MELITUS DENGAN METODE REGRESI COX PROPORTIONAL HAZARD PADA DATA SATU PARAMETER TERSENSOR TIPE II — Zulfa Bariyyah, Bq. Yulia Setia Silviani, et al. · Jurnal Eksbar (2025) | TGRS Research Map | TGRS