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p-Index From 2021 - 2026
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This Author published in this journals
All Journal UNP Journal of Statistics and Data Science
Andini Diva Luthfiyah
Universitas Negeri Padang
Computer Science & IT Decision Sciences, Operations Research & Management Mathematics Social Sciences

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Regresi Data Panel dengan Kesalahan Standar Driscoll-Kraay: Analisis Kejahatan dan Indikator Sosial Ekonomi di Sumatera Barat (2017–2024) Andini Diva Luthfiyah; Dhio Ervandi; Tessy Octavia Mukhti
UNP Journal of Statistics and Data Science Vol. 4 No. 2 (2026): 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/vol4-iss2/479

Abstract

Criminal behavior is a complex social issue that threatens public safety and hinders regional development. In Indonesia, the crime rate varies across provinces and is influenced by multiple socioeconomic and structural factors. In West Sumatra Province, fluctuations in crime risk over time highlight the need for a deeper analysis of its determining factors. Understanding these factors is essential for the government to formulate effective and targeted crime prevention policies. This study aims to analyze the determinants of crime risk in West Sumatra Province using panel data from 2017 to 2024, covering 19 districts and cities, allowing for a more robust and comprehensive evaluation of both temporal and cross-sectional variations. The variables examined include the open unemployment rate, poverty rate, percentage of youth not in employment, education, or training (NEET), and the COVID-19 pandemic as a dummy variable. Panel data regression analysis was employed, and the results indicate that the most appropriate model is the Random Effects Model (REM). The findings show that the open unemployment rate and the pandemic variable have a significant effect on crime risk at the 5% significance level, while the poverty rate is significant at the 10% level. These results provide valuable insights for policymakers in addressing the root causes of crime in West Sumatra through employment generation, poverty alleviation, and preparedness for crisis situations.
Stratified Cox Regression Approach to Identifying Prognostic Factors for Survival in Breast Cancer Patients Dhio Ervandi; Aisyah Novriani; Andini Diva Luthfiyah; Fauzan Al Hamdani Siregar; Tessy Octavia Mukhti
UNP Journal of Statistics and Data Science Vol. 3 No. 4 (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-iss4/418

Abstract

The most common type of cancer that affects women is Breast cancer. In 2022, 2.3 million women were diagnosed with breast cancer, and 670,000 deaths were recorded globally. By 2040, it is estimated that breast cancer will increase by 40%, reaching 3 million annually with the number of deaths increasing by 50% to 1 million in 2020. This highlights breast cancer as a serious threat to world health. This study utilized secondary data from METABRIC or the Molecular Taxonomy of Breast Cancer International Consortium obtained from the website www.kaggle.com/datasets/raghadalharbi/breast-cancer-gene-expression-profiles-metabric/data. The independent variables analyzed were, Age at Diagnosis (X­­1), Surgery Type (X­­2), Chemotherapy (X­­3), Hormone Therapy (X­­4), Tumor Size (X­­5), Radio Therapy (X­­6), Pam50. The dependent variables were Survival Time (Overall Survival Month) and Patient Status. In this study, we used the Stratified Cox model to predict the predictor variables of survival time. The total number of patients used was 18886, with 1080 censored patients and 788 uncensored patients. The Stratified Cox model without interaction revealed that the patients who underwent breast-conserving surgery had a 1.35 times higher risk of death compared to those who underwent mastectomy. Patients who received chemotherapy had a 2.01 times higher risk of death than those who did not, while patients who did hormone therapy had a 1.83 times higher risk of death than those who did not undergo this therapy.
An Examination of Determinants Affecting the Survival Duration Pediatric Brain Cancer Patients Through Stratified Cox Regression Analysis Fauzan Al-Hamdani Siregar; Andini Diva Luthfiyah; Tessy Octavia Mukhti; Dony Permana
UNP Journal of Statistics and Data Science Vol. 3 No. 4 (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-iss4/420

Abstract

Brain cancer is the second most common pediatric malignancy and the leading cause of cancer-related mortality in children. Pediatric brain tumors (PBTs) represent around 25% of all pediatric cancers and consist of clinically and biologically diverse subtypes, with an estimated incidence of 0.3–2.9 cases per 100,000 children annually. The high prevalence emphasizes the importance of identifying factors that influence patient survival. This study aims to identify and analyze the factors that significantly affect the survival duration of pediatric brain cancer patients by applying the Stratified Cox regression model. This study utilized secondary data from the Pediatric Brain Cancer database (www.cbioportal.org). Independent variables included cancer type, ethnicity, other medical conditions, sex, tumor type, and treatment type, while the dependent variables were survival time (OS Months) and patient status (OS Status). Data were analyzed using the Stratified Cox regression method. A total of 203 patients were observed, consisting of 39 uncensored cases (19.21%) and 164 censored cases (80.79%). The majority of patients were male (58.62%), diagnosed with low-grade glioma/astrocytoma (43.35%), classified as non-Hispanic or Latino (93.52%), had no additional medical conditions (51.72%), received new treatment (85.22%), and were categorized with primary tumor type (74.38%). Results from the stratified Cox model indicated that cancer type was a significant predictor of survival. Children with embryonal tumors were found to have 8.9 times greater risk of experiencing an event compared to those with CNS cancer types, whereas children with high-grade glioma/astrocytoma had a 24.85 times higher risk compared to the CNS cancer group.
Co-Authors Aisyah Novriani Dhio Ervandi Dony Permana Fauzan Al Hamdani Siregar Fauzan Al-Hamdani Siregar Tessy Octavia Mukhti