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Journal : JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI

Pemodelan Penderita Tuberkulosis di Jawa Timur Berdasarkan Pendekatan Geographically Weighted Regression (GWR) Diah Puspita Ningrum; Toha Saifudin; Suliyanto Suliyanto; Nur Chamidah
Jurnal Matematika, Statistika dan Komputasi Vol. 19 No. 1 (2022): SEPTEMBER, 2022
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v19i1.21262

Abstract

Tuberculosis is the 13th trigger of death causes around the world. Even after Covid-19, tuberculosis ranks 2nd as a contagious killer disease. In 2020, Indonesia ranks 2nd out of 8 countries with the highest contributor to tuberculosis sufferers after India. East Java Province is the region with the largest number of tuberculosis cases in order of 8. Tuberculosis cases in East Java in 2020 have decreased, but when viewed from the success rate of treatment of tuberculosis cases per district/city in East Java, it was found that 53% still did not meet the target of 90%. According to (World Health Organization), gender affects the occurrence of tuberculosis disease, where men are more susceptible than women. In finding treatment for all tuberculosis incidents in East Java, the highest patient was male. This study was conducted to model tuberculosis in men in the East Java area. The results of the study prove that the modeling of male tuberculosis in East Java used linear regression and GWR  (Geographically Weighted Regression) obtained the best model was GWR with Fixed Gaussian Kernel weighting, CV value of 5.68, and R2 86.47%. Variables that have a significant effect on male tuberculosis in East Java are BCG immunization for male infants, public places meeting health requirements, youth who smoke tobacco every day, sex ratio, and households with access to proper sanitation facilities.      
Classification Of Country Status In 2022 Based On Social Indicators With Ordinal Logistic Regression Sugha Faiz Al Maula; Alfi Nur Nitasari; Mochamad Rasyid Aditya Putra; Maelcardino Christopher Justin; Salma Bethari Andjani Sumarto; Suliyanto Suliyanto; Toha Saifudin
Jurnal Matematika, Statistika dan Komputasi Vol. 20 No. 3 (2024): May 2024
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v20i3.32356

Abstract

This research examines the classification of country status in 2022 by applying ordinal logistic regression on various social indicators including education, health and economic. The urgency of the research is to know the country determine factors with specific factors in the form of research variables that can be useful for policy makers, unlike the existing classification which is only divided based on GDP per capita or HDI score only. By dividing 3 country status classes, namely not developed, developing and developed countries using the world bank classification baseline, the accuracy results were obtained at 72,5% but there were several variables that were not significant. After re-modelling, the accuracy was found increased to 76.4% with the odds ratio results for the minimum wage variable being 42,32 in the high class compared to the middle class and 11,66 for the middle class compared to the lower class, which means that the higher the minimum wage tends to be classify countries as developed countries. Another variable that has significance level is the birth rate with an odds ratio of 0,71 in the high and middle classes and 0.89 in the middle and lower classes comparison, which shows that this variable has a negative effect because the odds ratio is <1, which means that the higher the birth rate tends to make the country will be classified as a non-developed country.