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RAGAM: Journal of Statistics and Its Application
Published by Universitas Lambung Mangkurat
ISSN : -     EISSN : 29628539     DOI : https://doi.org/10.20527/ragam.vXXX
Core Subject : Economy, Humanities, Health, Science, Education,
Humanities Computer Science & IT Economics, Econometrics & Finance Mathematics Public Health
RAGAM Journal publishes scientific articles in the field of statistics and its applications, including: * Biostatistics * Parametric and nonparametric statistics * Quality control * Econometrics and business * Industrial statistics * Time series analysis * Spatial statistics * Data mining * Computational statistics * Applications of statistics in the medical, economic, social, environmental, industrial, technological, and other related fields
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 2 Documents
 1 
Search results for , issue "Vol 5, No 1 (2026): RAGAM: Journal of Statistics " : 2 Documents clear
APPLICATION OF PANEL VECTOR AUTOREGRESSIVE (PVAR) MODEL ON THE ANALYSIS OF INFLATION AND GDRP RATE Nusyirwan, Nusyirwan; Khairunnisa, Khairunnisa; Nisa, Khoirin; Misgiyati, Misgiyati
RAGAM: Journal of Statistics & Its Application Vol 5, No 1 (2026): RAGAM: Journal of Statistics & Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v5i1.17067

Abstract

PVAR is an extension of the VAR model applied to panel data, combining time series with cross-sectional data from various regions. This model enables all variables to be treated as endogenous and analyzed simultaneously. This study aims to examine the relationship between inflation and economic growth (GRDP) across Indonesian provinces using the Panel Vector Autoregressive (PVAR) model. The analysis includes stationarity testing (IPS test), optimal lag selection (MMSC), and parameter estimation using the Generalized Method of Moments (GMM). The validity of instruments is assessed through the Sargan-Hansen test, while causal relationships are analyzed using the Granger causality test. Results indicate a bidirectional relationship between inflation and economic growth in several provinces. The model is proven to be stable. Furthermore, the Impulse Response Function (IRF) and Forecast Error Variance Decomposition (FEVD) analyses illustrate how shocks to one variable influence the other over time. These findings are expected to contribute to more effective formulation of regional economic policies.
MODEL REGRESI COX PROPORTIONAL HAZARD DENGAN PENDEKATAN DISTRIBUSI POISSON PADA LAJU SURVIVAL PASIEN HIV/AIDS Amaludin, Ahmad; Hakim, Raihan Nuur; Arifin, Samsul
RAGAM: Journal of Statistics & Its Application Vol 5, No 1 (2026): RAGAM: Journal of Statistics & Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v5i1.18041

Abstract

Human Immunodeficiency Virus (HIV) and Acquired Immune Deficiency Syndrome (AIDS) represent a global health crisis requiring long-term management. Understanding the factors influencing patient survival duration is crucial for effective clinical management. This study aims to model the survival rate of HIV/AIDS patients and determine dominant risk factors using Cox Proportional Hazard regression. This study utilized secondary data from the ACTG 175 clinical trial involving 2,139 patients. Parameter estimation was performed using the Maximum Partial Likelihood method, validated by the Schoenfeld residuals test. The results indicated that the Proportional Hazard assumption was met for all research variables. Simultaneously, the predictor variables significantly influenced the model. Partial testing identified Didanosine combination therapy (HR=0.715) and a history of drug use (HR=0.720) as protective factors. Conversely, clinical symptoms (HR=1.773), a history of Zidovudine use (HR=1.605), and low Karnofsky scores (HR=1.403) were identified as primary risk factors. Treatment factors and clinical conditions proved to have a more dominant influence on survival rates compared to demographic factors.

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