Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS
Meilawati, Nadia Lutfi
Unknown Affiliation
Computer Science & IT

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

Found 2 Documents
Search

 1 
Spatial Model for Food Security in Eastern Indonesia 2024 Shohwah, Fathiyah Nur; Arufi, Imam Fathoni; Wicaksono, Mohammad Iqbal; Meilawati, Nadia Lutfi; Meilani, Nilam Cahya; Sohibien, Gama Putra Danu
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2025 No. 1 (2025): Proceedings of 2025 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2025i1.468

Abstract

Food security is the condition of meeting food needs for the country down to the individual level, as measured by the availability, affordability, utilization, and stability of food. Despite being a basic human need, food security in Indonesia is not evenly distributed, especially in Eastern Indonesia. Based on these findings, this study aims to determine the general picture of food security and the factors influencing it in districts/cities in Eastern Indonesia in 2024. The method used is the Spatial Durbin Model (SDM) with an inverse distance weighting matrix. The results show that the variables Distribution of GRDP of Sector Agriculture, Forestry and Fishing, Poverty Rate, Average Years of Schooling, Lag of Food Security Index, Lag of Open Unemployment Rate, and Lag of Poverty Rate have a significant influence on the Food Security Index variable in districts/cities in Eastern Indonesia in 2024.
Application of the Geographically Weighted Negative Binomial Regression (GWNBR) Method to Tuberculosis Cases in North Sumatra Province in 2024 Tinambunan, Titin Julianti Br; Nufus, Nisa Hayatun; Meilawati, Nadia Lutfi; Rahma, Rezky; Wicaksono, Febri
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2025 No. 1 (2025): Proceedings of 2025 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2025i1.474

Abstract

Tuberculosis is one of the leading causes of death worldwide. Approximately 1.2 million deaths occur annually due to tuberculosis. According to the World Health Organization (WHO), Indonesia is the second-largest tuberculosis country after India, with a 10% prevalence rate (WHO, 2024). According to Ministry of Health data, in 2024, North Sumatra was the province with the highest number of TB cases on Sumatra Island, with several cases above the national average, ranking third in Indonesia. The number of tuberculosis cases in North Sumatra is census data and is overdispersed, with spatial influences. Therefore, the method used is Geographically Weighted Negative Binomial Regression (GWNBR), which produces local parameters. The results show that GWNBR forms eight regional groups based on significant variables. Rainfall and per capita expenditure variables have a significant influence in all districts/cities, and the percentage of BCG immunizations and the percentage of smoking population have a significant influence in almost all regions. Meanwhile, health fund allocation only shows a significant influence in several districts/cities. The AIC value of the GWNBR is not smaller than the AIC value of the negative binomial regression. However, the GWNBR model can be used to examine the influence of independent variables on tuberculosis cases spatially in North Sumatra.
Co-Authors Arufi, Imam Fathoni Meilani, Nilam Cahya Nufus, Nisa Hayatun Rahma, Rezky Shohwah, Fathiyah Nur Sohibien, Gama Putra Danu Tinambunan, Titin Julianti Br Wicaksono, Febri Wicaksono, Mohammad Iqbal