Article Per Year (5 Year)
p-Index From 2020 - 2025
0.408
P-Index
This Author published in this journals
All Journal Indonesian Council of Premier Statistical Science
Ramadhani, Hilvania
Unknown Affiliation
Computer Science & IT Economics, Econometrics & Finance Mathematics Public Health Social Sciences

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Estimation of Hazard Cumulative Function Using the Nelson-Aalen Method on Covid-19 Patient Data in Jember Regency Ramadhani, Hilvania; Pauziah, Rini
Indonesian Council of Premier Statistical Science Vol 4, No 1 (2025): February 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/icopss.v4i1.37519

Abstract

The Covid-19 pandemic presents a major challenge in the health sector, especially related to understanding patient recovery patterns. This study aims to estimate the cumulative hazard function using the Nelson-Aalen method on the length of treatment data of Covid-19 patients who have recovered in Jember Regency. The Nelson-Aalen method is a non-parametric approach that does not require certain distribution assumptions and is suitable for survival data, especially those subjected to right censorship. In this study, all patient data was complete without sensors. The analysis was performed with R software, resulting in a cumulative hazard curve that showed an increased risk of recovery as the treatment time increased. The results of this study provide an empirical picture of patient recovery patterns and serve as a basis for evaluating health service efficiency and hospital capacity planning during the pandemic. In addition, the application of the Nelson-Aalen method reinforces the contribution of non-parametric statistical methods in epidemiological studies
Forecasting of Average Air Temperature in the City of Pekanbaru Using the Holt-Winters Method Yendra, Rado; Marizal, Muhammad; Ramadhani, Hilvania
Indonesian Council of Premier Statistical Science Vol 4, No 2 (2025): August 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/icopss.v4i2.37868

Abstract

Global climate change causes significant fluctuations in air temperature, including in the city of Pekanbaru, therefore, a predictive system is needed that can help the government and the community in dealing with climate impacts, one of which is through air temperature forecasting. This study aims to forecast the average air temperature in Pekanbaru City using the Holt-Winters Exponential Smoothing method, which is known to be effective in capturing seasonal patterns and trends. The data used is monthly average air temperature data from 2017 to 2024 obtained from BMKG. The analysis was carried out using an addictive approach and model evaluation was carried out based on the Mean Absolute Percentage Error (MAPE) value. The results show that the best model is obtained on a parameter with a MAPE value of 2.684. This model is then used to forecast the air temperature in 2025, which is predicted to decrease gradually. The results of this forecast are expected to be a reference in planning and decision-making related to climate change mitigation in the Pekanbaru area
Co-Authors M Marizal Pauziah, Rini Yendra, Rado