Author:
Wijaya A P,Nugraha A L,Sukmono A,Firdaus H S
Abstract
Abstract
The demography database system should be very useful for various purposes in resolving socio-economic problems, such as the distribution of charity, especially for people affected by the Covid-19 pandemic. But unfortunately, the demography database system in Indonesia still has many problems. Things to consider are that there is no integration between databases at the central and local governments, and there is no synchronization of data between institutions. The next problem is that our demographic database system is not based on spatial information. Therefore, we need a demography database system that is integrated with the spatial information system. This study aims to integrate a demographic database system into a spatial information system. The demographic database system in principle always refers to certain administrative units, such as villages, subdistricts, districts/cities, and the state. The administrative unit can contain information about a geographic perspective, such as elevation, position, topography, etc. As a result, in addition to demographic policies, geographic perspectives can be considered, and the identification of asynchronous data between central and local governments becomes easier. In addition, there are impacts, which need to be considered in transforming tabular to spatial data, such as; scale factor, generalization, and classification.
Reference18 articles.
1. Ego Sektoral, Penyebab Belum Terintegrasi Basis Data Kependudukan;Ridwan,2021
2. Quantitative assessment of social vulnerability for landslide disaster risk reduction using gis approach (case study: Cilacap regency, province of central Java, Indonesia);Wijaya;International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences-ISPRS Archives,2018
3. Effectiveness Of Classification Method And Color Symbol Scheme On Choropleth Map Of Population Density In Special Region Of Yogyakarta;Afifah,2019
4. What is a dashboard—ArcGIS Dashboards,2010
5. A data cube design and construction methodology based on OLAP queries;Djiroun,2016