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Pengelompokan Kejadian Stunting di Indonesia pada Tahun 2022 dan Faktor-faktor yang Memengaruhinya: Sebuah Gambaran Putri, Aida Devanty; Maulidia, Sopa
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.v2024i1.1972

Abstract

Stunting can have a significant impact on the development of human resources in Indonesia. This condition can be a threat to achieving sustainable development. This study aimed to clustering the incidence of stunting and analyze its determinants based on the direct causes of stunting. The data we uses come from Statistics Indonesia and the Ministry of Health’s SSGI report 2022. We perform a clustering analysis using k-means method for descriptive analysis while inferential analysis is described through multiple linear regression model. The result of the study show that there are two clusters formed and three variables that significantly affect the incidence of stunting in Indonesia, which are Low Birth Weight (BBLR), Access to Safe and Appropriate Sanitation, and Complete Immunization. The findings of this study are expected to provide a robust scientific basis for the development of more efficient health policies and programs aimed at reducing stunting in Indonesia.
Peramalan Produksi Beras Indonesia Tahun 2024: Pemenuhan Target Produksi Beras Nasional dan Upaya Mencapai Kemandirian Pangan Putri, Aida Devanty; Haya, Aqilla; Crisanty, Tengku Mashitah
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.v2024i1.1994

Abstract

To ensure food independence, achieving production sufficiency is essential. The government has targeted rice as the primary commodity for self-sufficiency. This study aims to estimate rice production up to December 2024 to evaluate Indonesia’s potential in achieving food independence through the 2024 rice production target. Utilizing rice production data from 2019 to April 2024 provided by BPS-Statistics Indonesia, the study employs SARIMA model (2,0,0)(0,1,1)12. The findings suggest that rice production in Indonesia is projected to reach only approxiamtely two-thirds of the national production target for 2024, and indicating a decreased in rice compared to 2023. The literature review underscores the need for strategies such as increasing the availability of land rice cultivation, diversifying food source to reduce dependence on rice, and the implementing technological innovations and information systems to enhance food diversity.
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.