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Implementation Of One Indonesian Data for An Integrated Official Statistical System Maulana, Alfarizi Rehan
Educational Studies and Research Journal Vol. 1 No. 1 (2024): Educational Studies and Research Journal
Publisher : MID Publisher International

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60036/tykdbn37

Abstract

The necessity of each institution in meeting its data requirements raises uncertainties in data governance. Various data versions of the same object create doubts about selecting valid data. Consequently, Presidential Regulation No. 39 of 2019 concerning One Data Indonesia (SDI) was issued, emphasizing the coordination and collaboration of ministries and institutions with other statistical producers, including the Central Statistics Agency, to generate data. This aims to prevent data duplication, ensuring a singular, complete, and valid dataset. Therefore, this study seeks to elucidate SDI and its outcomes in a region that has implemented SDI. The research methodology involves a literature review drawing from various sources on SDI. The study concludes that the implementation of the One Data Indonesia system is crucial to prevent data duplication and enable centralized integration, thereby enhancing data governance quality.
Analisis Heterogenitas Spasial Tingkat Pengangguran Terbuka di Pulau Jawa Tahun 2024: Pendekatan Geographically Weighted Regression Prayoga, Angga; Maulana, Alfarizi Rehan; Falson, Jauzie
Seminar Nasional Official Statistics Vol 2025 No 1 (2025): Seminar Nasional Official Statistics 2025
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2025i1.2418

Abstract

Java Island is the center of the Indonesian economy with its largest contribution and high population density. However, unemployment remains a problem, and each region has different local characteristics. The indicator for measuring unemployment is the Open Unemployment Rate (TPT). Therefore, this study aims to determine the overview and factors influencing unemployment in districts/cities on Java Island, taking into account spatial heterogeneity in 2024. The data used are sourced from the Statistics Indonesia (BPS). The analytical method used is Geographically Weighted Regression (GWR). The results show that unemployment in each district/city is influenced by different factors. The TPAK and UMK have the greatest influence on the TPT in districts/cities on Java Island in 2024. The government needs to take a broader and more comprehensive approach to addressing unemployment, taking into account the specific conditions of each region.