  The transparency nature of Open Data is beneficial for citizens to evaluate
government work performance. In Indonesia, each government bodies or ministry
have their own standard operating procedure on data treatment resulting in
incoherent information between agent and likely to miss valuable insight.
Therefore, our motivation is to show the advantage of Open Data movement to
support unified government decision making. We use the dataset from data.go.id
which publish official data from each government bodies. The idea is by using
those official but limited data, we can find important pattern. The case study
is on Human Development Index value prediction and its clustered nature.
  We explore the data pattern using two important data analytics methods
classification and clustering procedure. Data analytics is the collection of
activities to reveal unknown data pattern. Specifically, we use Artificial
Neural Network classification and K-means clustering. The classification
objective is to categorize different level of Human Development Index of cities
or region in Indonesia based on Gross Domestic Product, Number of Population in
Poverty, Number of Internet User, Number of Labors and Number of Population
indicators data. We determined which city belongs to four categories of Human
Development stated by UNDP standard. The clustering objective is to find the
group characteristics between Human Development Index and Gross Domestic
Product.
