Construction projects on soft soils face significant technical and financial challenges due to low soil bearing capacity and high potential for settlement. These unique characteristics require effective integration of design and implementation to overcome high risks and improve structural stability. This study develops a Decision Support System (DSS) model based on Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) applied to the process of selecting foundations and construction methods for buildings on soft soils. This DSS enables a comprehensive assessment of various design alternatives and construction methods based on multi-aspect criteria, including stability, cost, time, material, and environmental conditions. Through data analysis and questionnaires involving construction experts, this DSS was tested on an infrastructure project in the tidal area of South Kalimantan. The results show that this DSS model is effective in supporting the selection of foundations, such as piles and bored piles, which are adjusted to the building load and soil conditions. This DSS also provides implementation priorities that can minimize the risk of project costs and delays. In addition to improving efficiency and accuracy in decision making, this model offers an integrated approach that optimizes every stage of construction from planning to field execution. This DSS contributes to the development of better and more sustainable risk management methods in construction projects on soft soils. These findings are expected to be applied more widely in the construction industry, especially in efforts to manage the high risks associated with soft soil conditions and create more efficient and stable construction.