Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
P-Index
This Author published in this journals
All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan
Irfanullah, Asrul
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation

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

Found 2 Documents
Search

 1 
APPLICATION OF COX PROPORTIONAL HAZARD REGRESSION FOR ANALYZING FACTORS INFLUENCING THE RECOVERY RATE OF PULMONARY TUBERCULOSIS PATIENTS Irfanullah, Asrul; Damamain, Ferina Lestari; Tuanaya, Nur Amaliya
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 2 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss2pp0987-0996

Abstract

Pulmonary tuberculosis is a serious disease that requires special attention from the community and the Government of Indonesia, especially the Maluku Province. One commonly used analytical method in the health field is survival analysis. Survival analysis is a statistical method related to observing the period until the occurrence of an event or events. This study aims to model and identify factors that affect the recovery rate of patients with pulmonary tuberculosis in Ambon City using Cox Proportional Hazard regression. The results of the Hazard Ratio interpretation show that the variables that have a significant influence are chest pain and night sweats. Specifically, patients experiencing chest pain exhibit a recovery rate 0.487264 times faster than those devoid of such symptoms. Similarly, patients experiencing night sweats demonstrate a recovery rate of 0.619839 times faster than their counterparts not experiencing this symptom. This study highlights the imperative of recognizing and addressing symptoms like chest pain and night sweats in managing pulmonary tuberculosis in Ambon City.
COMPARISON OF SURVIVAL ANALYSIS USING ACCELERATED FAILURE TIME MODEL AND COX MODEL FOR RECIDIVIST CASE Arfan, Nuraziza; Irfanullah, Asrul; Hamidi, Muhammad Rozzaq; Mukhaiyar, Utriweni
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 1 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss1pp629-642

Abstract

Recidivists, or ex-prisoners who commit crimes after serving a prior sentence, pose a critical challenge to the criminal justice system. This study examines social and economic factors that may reduce the likelihood of recidivists being re-arrested. Using survival analysis, the probability that a recidivist could survive in society without being re-arrested could be estimated. The purpose of this work is to compare the AFT and Cox models to determine which provides a better fit to identify factors affecting the likelihood of re-arrest within one year after release and to statistically assess the impact of these factors. This study utilizes a stratified Cox model to address variables that violate the proportional hazards (PH) assumption. The analysis is limited to four types of AFT models: Weibull, log-normal, log-logistic, and exponential. Results show that the stratified Cox model provides the best fit, based on Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). This demonstrates the Cox model's robustness in analyzing survival data, accurately approximating the distribution of survival times without restrictive assumptions, unlike AFT models. The study reveals that recidivists who received financial aid upon release have a lower risk of re-arrest compared to those who did not, and each additional prior theft arrest increased the risk of re-arrest by 1.09193 times.
Co-Authors Damamain, Ferina Lestari Hamidi, Muhammad Rozzaq Nuraziza Arfan Tuanaya, Nur Amaliya Utriweni Mukhaiyar