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p-Index From 2021 - 2026
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All Journal UNP Journal of Statistics and Data Science
Yoli Marda Novi
Universitas Negeri Padang
Computer Science & IT Decision Sciences, Operations Research & Management Mathematics Social Sciences

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Comparison of Cox Proportional Hazard Models with Interaction and Without Interaction in Heart Failure Patients Bunga Nafandra; Tessy Octavia Mukhti; Yoli Marda Novi; Nurul Mulya Syahwa; Olga Afrilly Putri
UNP Journal of Statistics and Data Science Vol. 3 No. 2 (2025): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol3-iss2/342

Abstract

 Heart failure is one of the disorders that attack the heart and is a major cause of morbidity and mortality. There is a 5% prevalence of heart failure in Indonesia in 2020. By utilizing survival analysis, this study aims to compare the Cox proportional hazard model with interaction and without interaction, and identify factors that significantly affect the survival time of heart failure patients. The research data is secondary data consisting of 299 heart failure patient data with several variables including high blood pressure, anemia status, and age. Through the stages of analysis that have been carried out, it is found that the variables of high blood pressure and age have a significant effect on the survival time of heart failure patients, while the anemia variable and the interaction between independent variables do not have a significant relationship with survival time. In addition, based on the AIC value, it is also found that the model without interaction is better than the model with interaction, which is characterized by a smaller AIC value in the model without interaction. Based on the best model, patients with high blood pressure have a 1.52 times higher chance of dying than patients without high blood pressure. In addition, the probability of death increased by 4.33% for every one-year increase in patient age. This study concludes that the model without interaction is more suitable for describing the relationship between independent variables and survival time in heart failure patients.
Comparison of Nadaraya-Watson Method with Local Polynomial in Modeling HDI and Poverty Relationship in Java Island Yoli Marda Novi; Fadhilah Fitri; Zamahsary Martha
UNP Journal of Statistics and Data Science Vol. 3 No. 3 (2025): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol3-iss3/380

Abstract

Poverty remains a critical issue in Indonesia, with the number of poor people reaching 24.06 million in September 2024. The Human Development Index (HDI), which indicates the level of human resource quality, is one of the factors influence poverty. This analysis focuses on the correlation involving HDI also this number of poor people in districts/cities in Java Island by comparing two kernel regresokesion methods, namely Nadaraya-Watson Estimator and Local Polynomial Estimator. Nonparametric regression was chosen thus it does not necessitate this presumption of a certain form of connection among variables, so it is more flexible in capturing complex relationship patterns. Secondary data from Statistics Indonesia (BPS) in 2024 was used in this study. Initial exploration shows, the data distribution does not have a clear pattern, so nonparametric methods are more suitable for use. Modeling is done using the optimal bandwidth obtained through the dpill function in R software. The analysis results show that the local polynomial estimator produces smoother regression curves and lower MSE values. In addition, comparison of different polynomial degrees shows that higher polynomial degrees tended to improve model performance. Among the tested polynomial degrees, the local polynomial with degree five (p=5) produced the lowest MSE value and the highest coefficient of determination. Therefore, the local polynomial estimator with degree 5 is the best method for modeling the relationship between the HDI and poverty levels in Java in 2024
Co-Authors Bunga Nafandra Fadhilah Fitri Nurul Mulya Syahwa Olga Afrilly Putri Tessy Octavia Mukhti Zamahsary Martha