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All Journal Parameter: Journal of Statistics Indonesian Journal of Statistics and Its Applications
Irfani, Rini
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Computer Science & IT Decision Sciences, Operations Research & Management Mathematics Other

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Fuzzy Clustering Algorithm to Catching Pattern of Change in District/City Poverty Variables Before and The Beginning of The Covid-19 Pandemic in Sulawesi Island Novidianto, Raditya; Irfani, Rini
Parameter: Journal of Statistics Vol. 1 No. 2 (2021)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (792.046 KB) | DOI: 10.22487/27765660.2021.v1.i2.15446

Abstract

The first goal of the SDGs is to end poverty in any form. The COVID-19 pandemic has greatly affected several economic indicators, especially absolute poverty, especially in Sulawesi Island, which has increased poverty indicators, leading to the movement of values between districts/cities. The grouping will show similar characteristics of absolute variable poverty. By the Fuzzy method clustering, each observation has a degree of membership so that from the degree of membership can be identified which areas have vulnerable to move from one cluster to another. Grouping using fuzzy algorithms will get an overview of districts of concern to the government during the pandemic so that the variable indicators of absolute poverty do not worsen due to the pandemic. Comparison with the absolute variables of poverty in 2019 and 2020 in the headcount index (P0), Poverty Gap Index (P1), and Poverty Severity Index (P2) in districts/cities on the island of Sulawesi based on silhouette coefficients shows that optimum clusters formed as many as 2 clusters, with a coefficient of 0.57 and 0.60 respectively. Cluster 1 has characteristics including areas with absolute poverty rates that tend to be more prosperous than cluster 2 in the 2019 and 2020 data groups on the island of Sulawesi. The fuzzy algorithm detects areas prone to displacement from cluster 1 to cluster 2, namely Bombana, Bone, Sangihe Islands, South Konawe, and Siau Tagulandang Biaro in 2019 and Bombana, Bone, Sangihe, and Maros Islands in 2020. The COVID-19 pandemic in March 2020 has not had much impact on the macro indicators of poverty seen in the transfer of membership from 2019 to 2020, which only occurred to 3 districts that changed, namely bolaang mongondouw and konawe selatan from cluster 1 to cluster 2 and Maros from cluster 2 to cluster 1.
Analyzing Low Birthweight in Java Based on Logistic Regression Model for Matched Pair Data: Analisis Berat Badan Lahir Rendah di Pulau Jawa Berdasarkan Model Regresi Logistik untuk Data Berpadanan Putri, Christiana Anggraeni; Irfani, Rini; Notodiputro, Khairil Anwar
Indonesian Journal of Statistics and Applications Vol 7 No 2 (2023)
Publisher : Statistics and Data Science Program Study, IPB University, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v7i2p75-85

Abstract

Low birthweight is one of the leading causes of neonatal death. Generally, the study of low birth weight is done by modeling logistic regression without considering the influence of confounding variables that can deviate the actual relationship between the explanatory variables and the response. This paper aims to identify low birth weight determinants in Java based on the logistic regression model for conditional study design, in which the analysis is based on matching the education level of the mother with one control. The results of the analysis showed that matched logistic regression can be used to correct bias due to the influence of a confounding variable. It reveals that based on the results of modeling, the frequency of pregnancy examinations and the parity of children are significantly affect the risk of low birth weight in Java Island.
Co-Authors Novidianto, Raditya Putri, Christiana Anggraeni