One of the strategic objectives of the Department of Public Works, in particular the Directorate General of Highways is to increase the percentage of roads in good condition. Meanwhile, the number and length of roads that need to be monitored continues to increase every year. The total length of roads in Indonesia based on data from the Directorate General of Highways in 2011 was approximately 38,570.00 km, and only 15,780.88 km that are on the good condition.[1] To manage the infrastructures mentioned above, the Directorate General of Highways periodically perform maintenance or repair depending on the level of damage. Meanwhile, to choose which road will be repaired first, the DGH had difficulty because there are several factors to consider include the level of damage, cost of repairs that are needed, the type of treatment required, the function and status of the road. Current conditions at the Department of Public Works, data management of road condition is still using paper documents and maps to show the location of roads that already surveyed. This poses problems when going to search the data to be used for the planning and analysis of the priority roads to be repair or maintenance. There are lots of roads that need to be analyzed, these problems will increase the length of the planning process and the results are less accurate. Therefore, it is necessary to build an information system that can help the Public Works Department in obtaining and analyzing information on the handling of road infrastructure. In this research, we developed decision support system using the analytic hierarchy process (AHP) and analytic network process (ANP). AHP and ANP are methods of multi-criteria analysis that can be use in the decision-making process. Those methods are use with respect to factors of perception, preference, experience and intuition. AHP and ANP incorporate assessments values and personal values into one logical way.[2] The functions contained in this system include road condition data input function using goggle map feature, the scoring function based on the criteria, the selection of analytical functions that will be prioritized, as well as report generation function based on the results of the analysis carried out in the form of tables and graphs.