Article Per Year (5 Year)
p-Index From 2020 - 2025
0.702
P-Index
This Author published in this journals
All Journal Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) Variance : Journal of Statistics and Its Applications Enthusiastic : International Journal of Applied Statistics and Data Science Jurnal KALANDRA
Madonna, Nora
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Mathematics Medicine & Pharmacology

Published : 4 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search

 1 
Premium Estimation Using a Spliced Gamma-Gamma Distribution for Long-Tail Insurance Claims Simanjuntak, Erica Grace; Madonna, Nora; Hayati, Ma'rufah
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 13 No 2 (2025): VOLUME 13 NO 2, 2025
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v13i2.60648

Abstract

Determining fair premiums that accurately reflect actual risks is a crucial element in insurance risk management, particularly when claim data exhibits long-tail characteristics that are challenging to model using a single distribution. This study aims to develop a premium estimation model using the spliced Gamma-Gamma distribution, which can capture the behavior of small to large claims more flexibly. This model is applied to a collective risk model framework, focusing on calculating the expected value and variance of aggregate claims as the basis for premium estimation. Premium estimation is conducted using three actuarial principles: the expected value principle, the variance principle, and the standard deviation principle. The research indicates that the standard deviation principle yields the most accurate premium estimation, as it accurately reflects the risk level while striking a balance between premium adequacy and affordability for policyholders. This approach considers both the expected loss and its volatility, making it more adaptive to extreme claim risks. This study demonstrates that claim modelling using splicing distributions, combined with volatility-based premium estimation principles, can be a practical and realistic approach to managing risk and estimating premiums more accurately.
ANALYSIS OF THE EFFECTIVENESS OF INFRASTRUCTURE DEVELOPMENT ON POVERTY LEVELS IN TANGERANG REGENCY IN 2024 Fitriawati, Andi; Virhafiyanti, Yunita; Madonna, Nora
VARIANCE: Journal of Statistics and Its Applications Vol 7 No 2 (2025): VARIANCE: Journal of Statistics and Its Applications
Publisher : Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/variancevol7iss2page175-186

Abstract

Poverty is defined as a condition in which a portion of the population lives with a monthly per capita expenditure below the poverty line. Addressing poverty remains a major challenge for sustainable development, and one strategic approach is infrastructure development. This study analyzes the effectiveness of education, health, and transportation infrastructure, as independent variables, in reducing poverty, as a dependent variable, in Tangerang Regency in 2024. The study employs multiple linear regression because it allows the simultaneous examination of the relationship between a single dependent variable and multiple independent variables. The results indicate that the three infrastructure variables simultaneously significantly affect poverty levels, as shown by an F-statistic of 3.572 and a p-value of 0.02813 at the 5% significance level. The coefficient of determination (R²) of 0.3001 suggests that infrastructure development explains 30.01% of poverty reduction, while other factors influence the remaining 69.99%. However, the partial test results show that none of the infrastructure variables individually has a significant effect on poverty. These findings suggest that infrastructure development contributes to poverty alleviation, though its sectoral impact remains limited. Enhancing equity and improving quality across infrastructure sectors are therefore essential to maximize and broaden its benefits.
Pelatihan Pemanfaatan Looker Studio dalam Analisis Data dan Dashboard Statistik bagi Peningkatan Kompetensi Siswa SMKS Nurul Huda Pringsewu Rosni; Mahrani, Dwi; Fitriawati , Andi; Sofia, Ayu; Yulita, Tiara; Irawan, Agus; Mt, Ma’rufah Hayati; Mahkya, Dani Al; Nasrullah; Simanjuntak, Erica Grace; Irfan, Miftahul; Madonna, Nora; Alfian, Muhammad Nuril; Siregar, Abian Avisena; Lestari, Yushinta Cahya
KALANDRA Jurnal Pengabdian Kepada Masyarakat Vol 4 No 6 (2025): November
Publisher : Yayasan Kajian Riset Dan Pengembangan Radisi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55266/jurnalkalandra.v4i6.605

Abstract

This Community Service (PkM) program aims to enhance students’ competencies in data analysis and statistical dashboard management through the utilization of the Looker Studio application. The training was conducted at SMKS Nurul Huda Pringsewu, involving students as participants. The training methods included lectures, demonstrations, and hands-on practice in processing data and presenting it in the form of interactive dashboards. The results of the program showed that students were able to understand the basic concepts of data exploration, the purpose of data visualization, and the use of key features in Looker Studio. In addition, students’ skills in selecting appropriate chart types according to analytical needs improved significantly. Based on the satisfaction survey, most participants rated the activity as very satisfactory (63%) and satisfactory (16%), although a small proportion expressed dissatisfaction (16%) or were not satisfied (5%). Overall, this PkM activity successfully contributed to improving students’ data literacy and digital skills, which are expected to support them in facing both academic challenges and the demands of a data-driven workforce
Log-Linear Analysis of the Association among Hematological Variables in Dengue Hemorrhagic Fever Cases Irfan, Miftahul; Hayati, Ma’rufah; Madonna, Nora; Dewi, Wardhani Utami
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 5 Issue 2, October 2025
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol5.iss2.art6

Abstract

Health data are often analyzed in their continuous form through approaches such as linear, logistic, or survival models. In this study, hematological variables were dichotomized based on established clinical cut-offs to enable log-linear analysis of associations among categorical variables, acknowledging the potential loss of information from this transformation. A log-linear model was applied to evaluate independence, dependence, and interaction patterns among leukocyte, hemoglobin, and hematocrit categories in a dengue hemorrhagic fever (DHF) patient dataset. Previous analyses using survival models identified these variables as factors associated with recovery rates; however, these models did not capture their interaction structure. Log-linear analysis was therefore employed to examine these associations more comprehensively. The best-fitting model was identified as , which included two-factor interactions between leukocyte–hematocrit and hemoglobin–hematocrit. This model demonstrated a good fit (Pearson , , ), including a three-factor interaction resulted in a saturated model (= 0) and did not improve model performance. These findings highlight significant interaction patterns among hematological variables in DHF patients, providing a more detailed understanding of their joint associations.
Co-Authors Agus Irawan Alfian, Muhammad Nuril Andi Fitriawati Dani Al Mahkya Dwi Mahrani Fitriawati , Andi Hayati MT, Ma’rufah Irfan, Miftahul Lestari, Yushinta Cahya Mt, Ma’rufah Hayati Nasrullah Rosni Simanjuntak, Erica Grace Siregar, Abian Avisena Sofia, Ayu Virhafiyanti, Yunita Wardhani Utami Dewi Yulita, Tiara