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All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Aplikasi Statistika & Komputasi Statistik Prosiding Seminar Nasional Official Statistics
Astuti, Erni Tri
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Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Social Sciences Transportation

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DAMPAK PANDEMI COVID-19 TERHADAP PENDAPATAN SEKTOR PENYEDIAAN AKOMODASI DAN MAKAN MINUM PROVINSI BALI Ahmad, Muhammad Ziyad; Astuti, Erni Tri
Jurnal Aplikasi Statistika & Komputasi Statistik Vol 15 No 1 (2023): Journal of Statistical Application and Computational Statistics
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/jurnalasks.v15i1.441

Abstract

The Covid-19 pandemic has caused a decline in the economy in Indonesia. This also happened in Bali, especially in the accommodation and food service sector which is one of the largest contributors to the GRDP of Bali Province. Therefore, this study aims to find out how and how big the impact of the Covid-19 pandemic on the sector of providing accommodation and food and drink. This study uses an intervention analysis method with a step function. The results of the study show that the Covid-19 pandemic has a significant direct impact on the GRDP of this sector, which is 15.22 percent. The worst impact occurred in the third quarter of 2021, which was 48.58 percent. The impact of the Covid-19 pandemic on the GRDP of the permanent accommodation and food and beverage sector until the end of 2021. This research is expected to be able to help the government and related sector business actors to take actions that are expected to reduce the impact of the Covid-19 pandemic.
Determinan Prevalensi Stunting di Nusa Tenggara Tahun 2023 Singrapati, Lalu Riza; Astuti, Erni Tri
Seminar Nasional Official Statistics Vol 2024 No 1 (2024): Seminar Nasional Official Statistics 2024
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2024i1.2077

Abstract

Indonesia is one of the countries still facing high prevalence rates of stunting. The Nusa Tenggara Archipelago significantly contributes to the high prevalence of stunting in Indonesia, with rates far above the national average. The factors causing the high prevalence of stunting in the Nusa Tenggara Archipelago need to be identified, considering the spatial aspects, as this region consists of many islands with diverse topographies and geographical characteristics. This study aims to identify the factors influencing the prevalence of stunting in the Nusa Tenggara Archipelago, taking into account the spatial aspects. The analysis method used is spatial regression analysis using the Spatial Error Model (SEM). The results of this study reveal that there is a spatial effect on the prevalence of stunting among children in the Nusa Tenggara Archipelago, indicated by a Global Moran’s I value of 0.420. The districts/cities with the highest stunting categories are mostly located in East Nusa Tenggara Province, with a rate of 50 percent, while in West Nusa Tenggara Province it is only 3.13 percent. Variables affecting stunting prevalence include the percentage of infants receiving early initiation of breastfeeding, the percentage of infants receiving exclusive breastfeeding, the percentage of children under five with a Child Health Book, average years of schooling for women, per capita expenditure, the percentage of households not using electricity, the prevalence of food insecurity, and the average fish consumption per capita per week. Based on the study results, government intervention is urgently needed to address the issue of stunting in the Nusa Tenggara Archipelago.
INCORPORATING COMPLEX SURVEY DESIGN FOR ANALYSING THE DETERMINANT OF WOMEN IN REPRODUCTIVE AGE PARTICIPATION IN FAMILY PLANNING PROGRAM IN INDONESIA Astuti, Erni Tri; Rahani, Rini; Pramana, Setia
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 3 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss3pp1401-1410

Abstract

Data generated from complex survey are often treated as un-weighted simple random samples by analyst. This is unfortunate because everyone has different probability to be selected as sample in each stage of the complex survey design. Fail taking it into account will have serious impact in parameter and variance estimation. This paper aims to examining relationship between participation in family planning program and socio demographic status of women in reproductive age in Indonesia used data from latest Indonesian’s Demographic and Health Survey (IDHS). IDHS employs a multi stage stratified sampling design, thus there are a number of weights included in public-use IDHS datasets to account for this complex sample design. We found that the complex design features of the IHDS increased the variance estimates of the estimated parameters in the logistic regression models by about 1.325 – 1.88 times, compared to a simple random sampling. Therefore, using variance estimated from un-weighted simple random samples would lead to wrong conclusion of the significance parameter suggested by the model. The result also found that all of socio demographics variables used as predictors are significant. Thus, women with moderate education, unemployment, exposed by media, living in rural community and wealthy, have spouse that have moderate education and have a job tend to participate in family planning program.
CLUSTERING OF FOOD SECURITY IN PAPUA ISLAND: WITH AN OPTIMIZED SPATIAL FUZZY CLUSTERING APPROACH Pasaribu, Rahmat Agung; Astuti, Erni Tri
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 4 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss4pp2411-2420

Abstract

Food needs are primary needs that must be met by everyone to maintain their survival. The condition of stable food security is still not evenly distributed throughout Indonesia. Papua Island is one of the regions that has low food security conditions. In identifying the characteristics of food security in Papua Island, it can be done using cluster analysis. The cluster analysis method used in this research is classical FGWC and FGWC with optimization of HHO. This method has considered the spatial element in the grouping process. The purpose of this study is to classify the level of food security in Papua Island and determine the effectiveness of using optimization in FGWC. Based on the evaluation results, it was found that the FGWC-HHO method was the most optimal method with a total of 3 clusters. Cluster 3 consists of 18 regencies is a cluster with a low level of food security, so this cluster can be used as a priority in handling the problem of food security which is still low in Papua Island.
DETERMINANTS OF POOR HOUSEHOLDS IN SOUTH SUMATRA USING A MULTILEVEL LOGISTIC MODEL Putri, Aida Devanty; Astuti, Erni Tri
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 2 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss2pp0773-0784

Abstract

Poverty is still one of the problems experienced by all countries, including Indonesia. According to BPS, in March 2021, the poverty rate in Indonesia was 10.14 percent. South Sumatra is a province with a poverty rate, which is the tenth-highest nationwide and the third-highest on Sumatra Island. This poverty rate is accompanied by a contraction in economic growth in 2021 by 3.58 percent. This condition indicates a contradiction and suggests that poverty still needs to be resolved. Moreover, the disparity in social and economic aspects across regions could potentially make the poverty rate high. This research aims to see the individual and regional or contextual factors affecting poor households. To simultaneously capture the effects of individual and regional level, we perform a Multilevel Logistic model using hierarchical structured poverty data from SUSENAS. The result shows that 4 (four) variables at individual level, which are the number of household members, the status of residence building, health insurance, and saving ownership, had a significant effect on the poor household. The region with high unemployment rate tend to have a high percentage of poor households. This result indicates that local government need to have policies that can affect poor households directly, such as socializing more about health insurance program and family planning program, as well as supervision in social aid distribution. Moreover, they need to create a program that can employ more people in order to decrease the percentage of poor households in such regions.
Co-Authors Ahmad, Muhammad Ziyad Pasaribu, Rahmat Agung Pramana, Setia Putri, Aida Devanty Rini Rahani Singrapati, Lalu Riza