Article Per Year (5 Year)
p-Index From 2021 - 2026
1.116
P-Index
This Author published in this journals
All Journal Al-Jabar : Jurnal Pendidikan Matematika Desimal: Jurnal Matematika Communication in Biomathematical Sciences
Rachmawati, Ro'fah Nur
Unknown Affiliation
Education Mathematics Social Sciences

Published : 5 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 5 Documents
Search

 1 
Utilize imagery and crowdsourced data on spatial employment modelling Pusponegoro, Novi Hidayat; Rachmawati, Ro'fah Nur; Siallagan, Maria A. Hasiholan; Wicaksono, Ditto Satrio
Al-Jabar: Jurnal Pendidikan Matematika Vol 15 No 2 (2024): Al-Jabar: Jurnal Pendidikan Matematika
Publisher : Universitas Islam Raden Intan Lampung, INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ajpm.v15i2.24518

Abstract

Background: Spatial employment modeling investigates employment distribution, patterns, influencing factors, neighboring area impact, and regional policy efficacy. Conventional studies often rely on traditional data sources, which may overlook critical employment-related phenomena. In 2022, Java recorded the lowest labor absorption rate in Indonesia, necessitating a new approach.Aim: This study combines imagery, crowdsourced data, and official statistics to identify factors influencing labor absorption in Java Island.Method: Geographically Weighted Regression (GWR) was employed to account for spatial effects in the data.Results: The model reveals that nighttime light intensity in urban and agricultural areas, along with environmental quality, significantly enhances labor absorption across Java. Internet facilities, universities, and the number of micro and small industries also positively influence most districts/cities.Conclusion: Incorporating new data sources offers valuable insights for understanding employment patterns and can enrich employment research frameworks.
The influence of climate change and country-based conflict on crop production: Evidence based on global panel data in the last decade Rahman, Juli Yandi; Rachmawati, Ro'fah Nur; Nugraha, Arya Muditama; Widjanarko, Farrell Tajusalatin
Desimal: Jurnal Matematika Vol. 6 No. 2 (2023): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v6i2.18928

Abstract

In the past decade, the food crisis has become a special concern for the international community. This is in the spotlight as the earth ages, increasingly changing climatic conditions lead to erratic crop yields and worsening crop quality. On the other hand, this condition is exacerbated by the increasingly tense dynamics of international politics which leads to conflict between countries. For this reason, we investigated the relationship between these conditions using the linear mixed model method. In this article, the model obtained is able to describe the real conditions currently occurring regarding the relationship between climate change, conflict between countries and crop production. Among other things, it is known that the majority of continents are carrying out agricultural extensions and intensifying efforts to reduce CO2 emissions, to increase crop production. On the other hand, as time goes by, the model shows that environmental temperature fluctuations are getting bigger. Apart from that, conflict factors apparently exacerbate the effects of climate change which directly affects crop production. This article also provides suggestions for countries on a continent to increase crop production while maintaining climate balance.
The effects of hydrometeorological disaster and potential conflicts on the human development index using linear mixed multilevel models Zevic, Farell Fillyanno; Rachmawati, Ro'fah Nur; Djunet, Ghina Nisrina; Almutawakkil, Fauzan Naufal
Desimal: Jurnal Matematika Vol. 6 No. 3 (2023): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v6i3.19514

Abstract

As is generally known, the human development index (HDI) is formed from three main factors, namely education, health, and income, which measure the population's access to a decent standard of living. Using the linear mixed multilevel models, this study indicates that other factors beyond these three basic dimensions of HDI, namely hydrometeorological disasters and potential conflicts, significantly affect the HDI value. This research focuses on longitudinal data analysis from 27 regencies and cities in West Java, Indonesia, in the last four years until 2022, with the level of hydrometeorological disasters consistently increasing every year and an increasing trend in the number of potential conflicts. The dimensions of human life and other factors can affect the human development index, namely the number of hydrometeorological disasters and potential conflicts, which have a negative correlation so that the value of the HDI can be reduced if the intensity of hydrometeorological disasters increases and possible conflicts can be controlled. Moreover, this study shows that uncontrolled potential conflicts in each regency or city from time to time can reduce HDI values. Therefore, this research can be a reference for the government, stakeholders, and the community in carrying out work programs that are right on target to increase HDI consistently every year.
Bayesian spatial data analysis: Application of pneumonia spread in west java Habsy, Muhammad Yusuf Al; Husein, Fulkan Kafilah Al; Yahya, Muhammad Harun; Rachmawati, Ro'fah Nur
Desimal: Jurnal Matematika Vol. 7 No. 1 (2024): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v7i1.23154

Abstract

Pneumonia has a notable influence on public health, especially among susceptible demographics like children and the elderly. This respiratory disease can be transmitted through human interaction. Analyzing the spread of the illness within a community requires assessing the characteristics of the community itself. The objective of this research is to describe the distribution of pneumonia cases and their causes in the West Java Province using RStudio software. The analytical method employed is the Integrated Nested Laplace Approximations (INLA) approach, a Bayesian statistical method used for estimation in complex Bayesian models, particularly in hierarchical or nested structure. The sample utilized comprises the entire population, totaling 27 Districts/Cities within West Java Province. The influence of differences in population size, number of people living in poverty, waste production, the quantity of primary healthcare facilities, total number of vehicles, and the count of HIV patients in Cities/Regencies in West Java on the spread of pneumonia will be analyzed. The result of analysis show that the population and number of health centers variables had a significant influence on the mapping of pneumonia disease in each location. And also, the Relative Risk (RR) and Standardized Incidence Ratio (SIR) maps show that some regions have a higher risk of pneumonia compared to other regions. These findings are expected to provide insights for public policies in addressing health issues, particularly in the efforts to prevent and control diseases like pneumonia. Moreover, these results serve as a foundation for further studies regarding other factors that might contribute to the spread of this disease at the local level.
Regresi Multiskala Tertimbang Geografis dan Temporal dengan LASSO dan Adaptif LASSO untuk Pemetaan Kejadian Tuberkulosis di Jawa Barat Habsy, Muhammad Yusuf Al; Rachmawati, Ro'fah Nur; Khotimah, Purnomo Husnul; Natari, Rifani Bhakti; Riswantini, Dianadewi; Munandar, Devi; Izzaturrahim, Muh. Hafizh
Communication in Biomathematical Sciences Vol. 8 No. 1 (2025)
Publisher : The Indonesian Bio-Mathematical Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/cbms.2025.8.1.6

Abstract

Tuberculosis (TB) is a global health issue caused by Mycobacterium tuberculosis and can affect any organ of the body, especially the lungs. The trend of TB cases varies between regions, and analytic assessment is required to identify the predictor variables. The purpose of this research is to compare the Multiscale Geographically and Temporally Weighted Regression (MGTWR) and the Geographically and Temporally Weighted Regression (GTWR) method, which both use Gaussian, Exponential, Uniform, and Bi-Square kernel functions, to identify significant variables in each region annually. The MGTWR method has the advantage of using a flexible bandwidth for each observation, that results in more accurate coefficient estimates. The sample used was 27 districts and cities in West Java Province, involving 36 variables divided into 5 dimensions, namely global climate, health, demography, population, and government policy, with a time span of 2019–2022. To overcome the problem of multicollinearity, the approach was carried out using the Least Absolute Shrinkage Selection Operator (LASSO) and Adaptive LASSO methods. In determining the best model, the prioritized criteria are to achieve the highest R2, which indicates the optimal level of model fit, as well as the smallest AIC, which indicates the most efficient model goodness of fit. The best model is MGTWR with LASSO variable selection on the Bi-Square kernel. This model has an R2 of 91.25% and the smallest AIC of 139.868. From the best model, each region emerged with a cluster structure affected by various variables from 2019 to 2022, providing an in-depth understanding of TB mapping that can assist in formulating more effective intervention measures.
Co-Authors Almutawakkil, Fauzan Naufal Devi Munandar, Devi Djunet, Ghina Nisrina Habsy, Muhammad Yusuf Al Husein, Fulkan Kafilah Al Izzaturrahim, Muh. Hafizh Khotimah, Purnomo Husnul Natari, Rifani Bhakti Novi Hidayat Pusponegoro Nugraha, Arya Muditama Rahman, Juli Yandi Riswantini, Dianadewi Siallagan, Maria A. Hasiholan Wicaksono, Ditto Satrio Widjanarko, Farrell Tajusalatin Yahya, Muhammad Harun Zevic, Farell Fillyanno