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Statistical Perspective of Dengue Hemorrhagic Fever in West Java: Insights from Two-Way RE Model Danarwindu, Ghiffari Ahnaf; Fadhlurrahman, Muhammad Ghani
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 4 Issue 2, October 2024
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol4.iss2.art4

Abstract

The Indonesian Ministry of Health has reported an alarming increase in Dengue Hemorrhagic Fever (DHF) cases, particularly in West Java Province. Given this trend, collaborative research and surveillance efforts are crucial to understanding and managing DHF cases in Indonesia. The panel data regression model in dengue fever cases will provide new insights into modeling. This research aimed to identify the most appropriate random effects model for estimating a dataset with four different variables. This study involved panel data variables on the effect of population density, percentage of poor people, percentage of households with access to clean water, and proper sanitation on DHF cases in West Java Province. This method emphasized selecting the best model from one-way and two-way Random Effects (RE) models and identifying what factors influenced the increase of DHF cases in West Java province. The best model obtained was a two-way RE Model with three significant variables. Based on the selected variables in the model, West Java Province needs to pay attention to the distribution of housing and economic activity in each district because population density is a crucial concern for the local government.
Geographically Weighted Regression with The Best Kernel Function on Open Unemployment Rate Data in East Java Province Putra, Robiansyah; Wahyuning Tyas , Sischa; Fadhlurrahman, Muhammad Ghani
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 2 Issue 1, April 2022
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol2.iss1.art4

Abstract

Unemployment is one of the problems that hinders employment development programs. Based on East Java BPS data, the Open Unemployment Rate in East Java in 2019 is about 3.92 percent. In 2020, unemployment increased by 466.02 thousand people and OUR increased by 2.02 percent to 5.84 percent in August 2020. In addition to the indicators that affect OUR, each observation location has different characteristics, so multiple linear regression modeling is not appropriate. Geographically Weighted Regression is one of the spatial analysis developed from multiple linear regression for data containing spatial heterogeneity effects. The weighting functions used for this GWR model are Kernel Fixed and Adaptive functions (Gaussian, Bi-Square, Tricube, and Exponential). The analytical step carried out in estimating the parameters is to use WLS. In the test, the best weighting was obtained, namely the Adaptive Tricube. Based on the results of the study, the GWR model with Adaptive Tricube weighted resulted in the value of R-Squared = 84.88%. However, the best model is obtained from the GWR model with exponential weighting with the smallest Akaike Information Criterion (AIC) value compared to the others, namely AIC = 86.01264 with R-Squared = 91.67.