Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal Unisda Journal of Mathematics and Computer Science (UJMC)
Melda Juliza
Universitas Jenderal Soedirman
Computer Science & IT Education Mathematics

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

Found 2 Documents
Search

 1 
Analisis Survival Menggunakan Regresi Eksponensial, Cox Proporsional dan Frailty pada Penderita TBC Felinda Arumningtyas; Melda Juliza; Sherly Steffiyani Askarilia
UJMC (Unisda Journal of Mathematics and Computer Science) Vol 11 No 1 (2025): Unisda Journal of Mathematics and Computer Science
Publisher : Mathematics Department, Faculty of Sciences and Technology Unisda Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52166/ujmc.v11i1.8912

Abstract

According to the WHO Global TB Report 2020, Indonesia is among the countries with the highest tuberculosis (TB) burden worldwide, with an estimated 845.000 people affected by TB and 98.000 deaths, which translates to 11 deaths per hour. However, only 67% of these cases have been identified and treated, leaving around 283.000 TB patients undiagnosed and untreated, putting them at risk of spreading the disease to others. This study aims to examine the factors that impact the recovery time of TB patients through Exponential regression and Cox Proportional Hazards (Cox-PH) regression. Additionally, unmeasured factors are incorporated into the model using the frailty model approach. The data used were medical records of 153 TB patients at Soehadi Prijonegoro Regional Public Hospital in Sragen. The study results show that the Cox-PH regression model yields a lower AIC value compared to the Exponential regression and frailty models, indicating that the survival analysis performance using the Cox-PH regression is superior to the other two models. Based on the Cox-PH regression modeling, the factors affecting the recovery duration of TB patients are comorbidities, previous cases, and diagnosis.
Peramalan Kemiskinan di Kabupaten Banyumas Menggunakan Regresi Nonparametrik dengan Pendekatan Kernel Nadaraya Watson Adjusted Novita Eka Chandra; Melda Juliza; Muhammad Hafidh Nashrullah
UJMC (Unisda Journal of Mathematics and Computer Science) Vol 11 No 1 (2025): Unisda Journal of Mathematics and Computer Science
Publisher : Mathematics Department, Faculty of Sciences and Technology Unisda Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52166/ujmc.v11i1.10646

Abstract

Poverty is a serious challenge faced by the Banyumas Regency Government. Although the poverty rate in this region has shown a declining trend for more than a decade, the pattern of decline has not been linear. This study utilizes time series data representing the percentage of the poor population in Banyumas Regency from 2003 to 2024. This research primarily seeks to forecast the poverty rate in 2030 and to differentiate between the performance of two kernel functions, Gaussian and Epanechnikov, which are applied in nonparametric regression using the adjusted Nadaraya-Watson kernel approach. Analysis results suggest that the model performs best when the bandwidth is set at its optimal value of 0,538909 using the Epanechnikov kernel function. Based on the forecast, the poverty rate in 2030 is estimated to be 12,87%. This result indicates the need for well-planned strategies and policies by the Banyumas Regency Government to reduce the poverty rate over the next six years.
Co-Authors Felinda Arumningtyas Muhammad Hafidh Nashrullah Novita Eka Chandra Sherly Steffiyani Askarilia