Visualising Indonesia’s Population Data with GIS


Visualising Indonesia’s Population Data with GIS

With economic, social, and political conditions constantly changing in Indonesia, government officials have found it increasingly challenging to set policies for the country. To tackle this, Indonesia’s Ministry of Home Affairs (KEMENDAGRI) needed access accurate, authoritative population data to guide policy decisions.

However, despite the implementation of its 2006 Population Administration regulation which collects population data from village to national level, the Indonesian government still lacked a system that could analyse this information. The process needed to be sped up, and government bodies also had to meet the increasing needs of spatial analysis in Indonesia. A map-based system was thus required to visualise the data.

To address this, Kemendagri started working with Esri Indonesia to build an information management system using Geographic Information System (GIS) technology.

The new system - called population data visualisation - incorporates characteristics of a population in a given area, such as the population size, age, household, income level, and other related demographic data gathered from the electronic single identity database (e-KTP) and Population Administration Information System (SIAK).

With the use of GIS, the system allows users to perform advanced spatial analysis that enables policy makers to identify patterns, trends, risks, and opportunities that static charts and graphs don’t reveal.

Thanks to GIS and the population data visualisation system, Kemendagri is now able to

  • Better diagnose problems and challenges that need to be addressed
  • Determine what alternatives exist to respond to these challenges
  • Make informed decisions from among these alternatives.

The system also plays a key in providing agencies with actionable information needed to support current and future initiatives, and to help guide policy-making decisions in Indonesia.

Visualising Indonesia’s Population Data with GIS