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All Journal EKO-REGIONAL JURNAL PENGEMBANGAN EKONOMI WILAYAH Economics and Finance in Indonesia PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS
Waris Marsisno
Politeknik Statistika STIS
Computer Science & IT Economics, Econometrics & Finance

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Availability of Infrastructure for Poverty Reduction in Indonesia: Spatial Panel Data Analysis Galih Pramono; Waris Marsisno
Economics and Finance in Indonesia Volume 64, Number 2, December 2018
Publisher : Institute for Economic and Social Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (12.003 KB) | DOI: 10.47291/efi.v64i2.587

Abstract

Poverty is a key issue in various developing countries, including Indonesia. One of the efforts to reduce poverty is building the infrastructure. Therefore, this study aims to determine the effect of infrastructure on the level of poverty by considering the spatial effect in the period 2011–2015. This study applies spatial panel data analysis with Spatial Autoregressive (SAR) model with fixed effect. The findings show that the infrastructure of electricity, health, sanitation, and building of senior high school has a significant negative impact on the percentage of the underprivileged people. Meanwhile, the building of elementary school has a significant positive impact on the percentage of the underprivileged people.
Labor Productivity Convergence in Indonesia: Spatially Dynamic Panel Data Analysis Ahmad Fajar Novianto; Waris Marsisno
EKO-REGIONAL Vol 14, No 2 (2019)
Publisher : Jurusan Ilmu Ekonomi dan Studi Pembangunan Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.erjpe.2019.14.2.1291

Abstract

The problem of labor productivity in Indonesia is a regional and sectoral inequality. To know the time required to remove inequality, can be measured by the level of convergence of labor productivity. The research would analyze the rate of sectoral labor productivity convergence among provinces in Indonesia spatially and identify the determinant factors of labor productivity. The analytical methods used is spatial dinamic panel data with Spatially Corrected Blundell-Bond (SCBB) estimation method. The results show that there are spatially sectoral labor productivity convergence. Primary sector takes the longest half-life convergence of 7-8 years, while secondary takes 1-2 years and tertiary sector takes 3-4 years. Furthermore, the Gross Capital Fixed Formation, Mean Years of Schooling, and real wage sectoral are significantly have positive affect to the labor productivity while Life Expectancy is significantly have negative affect to labor productivity.Keywords : convergence, spatial analysis, labor productivity
Logical Modelling of Statistical Data Using the SDMX Standard: Case Study on the Quarterly Gross Regional Domestic Product Table Kartika Amandasari; Nano Yulian Pratama; Farhan Satria Aditama; Waris Marsisno
Joint International Conference 2026: The 2nd Indonesia Forum on Labour and Productivity (IFLP) & The 4th International Conference on Data Science and Official Statistics (ICDSOS) Vol. 2025 No. 1 (2025): Proceedings of 2025 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2025i1.641

Abstract

Poverty, as a national issue, necessitates data-driven policy planning informed byaccurate and consistent statistics. To ensure the optimal quality and consistency of statistical datareporting across diverse regions, the adoption of an international standard is crucial. TheStatistical Data and Metadata Exchange (SDMX) standard facilitates the structured exchange ofdata and metadata. This study aims to design and implement a statistical indicator data modelusing the SDMX standard to improve table consistency. We utilized Quarterly Provincial GrossRegional Domestic Product (GRDP) data as a case study and applied the Design ScienceResearch Method (DSRM) as the methodology. The results demonstrate that modeling theGRDP data using SDMX yields a uniform and highly consistent table structure, significantlyenhancing the consistency of statistical data reporting across regions.
Estimation of Energy Transition Index based on Official Statistics and Satellite Imagery Data : (Case Study: Regencies/Cities in Indonesia) Sabilla Hamda Syahputri; Waris Marsisno
Joint International Conference 2026: The 2nd Indonesia Forum on Labour and Productivity (IFLP) & The 4th International Conference on Data Science and Official Statistics (ICDSOS) Vol. 2025 No. 1 (2025): Proceedings of 2025 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2025i1.724

Abstract

Energy has a crucial role in sustaining human life, its implementation should be optimized based on the principles of sustainable development through a shift from non-renewable to renewable sources. To monitor this shift, the World Economic Forum (WEF) developed the Energy Transition Index (ETI), which measures national-level transitions using conventional statistical data. However, the ETI is limited to the country level, while more detailed assessments are needed at smaller administrative scales such as regencies and cities to capture regional specificities. This study addresses the gap by constructing an energy transition index at the regency/city level in Indonesia for 2024. The analysis integrates official statistics with satellite imagery data to overcome limitations in subnational data availability. Methodologically, Exploratory Factor Analysis and uncertainty analysis were applied. Among five scenario of uncertaincy analysis tested, scenario 1 featuring min-max normalization, unequal weighting across indicators and factors, and linear aggregation produced the most reliable results. The findings reveal that the index is composed of four main factors. Overall, Indonesia’s energy transition index values show a relatively even distribution, yet disparities remain evident across islands and between regencies/cities. Higher scores are concentrated in the western regions, while lower scores dominate the eastern parts of the country.
Co-Authors Ahmad Fajar Novianto Farhan Satria Aditama Galih Pramono Kartika Amandasari Nano Yulian Pratama Sabilla Hamda Syahputri