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Determinan Produktivitas Pangan dan Konsumsi Kalori di Indonesia Tahun 2020 Siallagan, Maria Angelika H; Rahmah, Aisyah ‘Azizah Nur; Saputra, Martino Dwi; Hidayat, Ahmad Sovi; Arthamevia, Aisha; Budiasih, Budiasih
Seminar Nasional Official Statistics Vol 2023 No 1 (2023): Seminar Nasional Official Statistics 2023
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2023i1.1897

Abstract

One of the objectives in the Sustainable Development Goals (SDGs) agenda is to achieve the eradication of hunger, improve food security, enhance nutrition, and promote sustainable agriculture. However, environmental quality can influence the productivity and accessibility of food crops for communities. This study aims to investigate the impact of the environment on productivity and calorie consumption in 32 provinces of Indonesia using ensemble clustering and logistic regression with Penalized Maximum Likelihood Estimation (PMLE). The research findings indicate that 15 provinces in Indonesia have calorie consumption below the standard caloric sufficiency and exhibit below-average productivity for rice, corn, and chili compared to the national average. Furthermore, the logistic regression analysis with PMLE reveals that air and water quality positively and significantly influence food productivity and calorie consumption levels.
Aplikasi Regresi Data Panel Untuk Menganalisis Produktivitas Tenaga Kerja di Sulawesi Barat 2011-2023 Hidayat, Ahmad Sovi; Yuniasih, Aisyah Fitri
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.v2024i1.2047

Abstract

Economic development encompasses all efforts to enhance the economy of a country, thereby improving the welfare of its society. Economic growth can occur through increased productivity in generating the output. During 2011-2023, Sulawesi Island experienced the highest increase in labor productivity compared to other islands. However, West Sulawesi Province faced an issue where its labor productivity ranked 30th out of 34 provinces in 2023. This condition has implications for the low-income and welfare levels of its society. This study aims to analyze the general overview of labor productivity and analyze the factors affecting labor productivity in West Sulawesi from 2011-2023 using panel data regression. The study results show that labor productivity has gradually increased since 2011 but has started to slow down since 2020. The panel data regression analysis indicates that gross fixed capital formation, investment credit, the proportion of high school and above workforce, and health expenditure positively affect labor productivity.
LOCALIZED DATA FOR EDUCATIONAL EQUITY: SMALL AREA ESTIMATION OF OUT-OF-SCHOOL CHILDREN IN BALI AND NUSA TENGGARA Khairunnisa, Sherina Rafidah; Ubaidillah, Azka; Hidayat, Ahmad Sovi; Septiyana, Alya Nur; Putri, Shalihati Melani; Prananggalih, Ahmad Tegar; Kusuma, Arya Candra; Syahidah, Shafiyah Asy
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss2pp1179-1192

Abstract

This study aims to estimate the percentage of out-of-school children aged 7–17 years in Bali and Nusa Tenggara using the Small Area Estimation (SAE) method with a Hierarchical Bayes. One of the main challenges in education policy planning is the limited data available. National surveys, such as the National Socio-Economic Survey (Susenas), typically provide estimates only at the national and provincial levels, while more detailed data at the district level is often lacking. This limitation restricts the understanding of educational disparities at the local level and complicates the design of targeted policies. To address this issue, SAE Hierarchical Bayes provides a solution by producing more accurate district-level estimates, utilizing additional data without the need for new sampling. This method has proven to be cost-effective and efficient, particularly in regions with complex geography, such as Bali and Nusa Tenggara. The findings reveal that districts in East Nusa Tenggara generally exhibit a higher percentage of out-of-school children compared to the national average, indicating significant regional disparities that require attention. These findings highlight the urgency of improving educational infrastructure, particularly in underdeveloped areas of East Nusa Tenggara, to promote equitable access to education and reduce the number of children out of school