Indonesia is a country with large and dynamic economic activities reflected by an average economic growth reaching 6% per annum. Sunda Street Bridge (SSB) is one of the mega projects offered by the Indonesia government that would spend about US$ 25 billion. In line with the SSB main function as an efficient mean for transporting people and goods between two major islands in Indonesia, potential additional functions have been explored including installation of liquid and gas pipes, fiber optics, industrial area development and renewable energy utilization. This research establishes the approach to forecast demand in the case of conceptual design. The SSB is associated with innovations to determine the functions using value engineering methods. The approach involves forecasting demand with a System Dynamics simulation model that could provide a reliable estimate and generate scenarios to compare the financial feasibility of the project before and after the process involving innovation of project functions. Analysis involving demand forecasting with the System Dynamics Approach has confirmed that the Sunda Strait Bridge development with additional functions would increase the revenues of the overall project up to US$61.59 Million, in order to obtain an increased Internal Rate of Return (IRR) of the overall project up to 7.56% with a positive Net Present Value (NPV).
The development of a country is directly proportioned to its growing infrastructure needs. One of the most needed infrastructure in Indonesia is medical facility. The construction of public hospital especially in its tendering phase needs to refer to the stated presidential decree that includes a specific rule and policy. The tender process needs to be done carefully to ensure the most beneficial offer is selected. This research will utilize e-tendering method to select the right construction partner. The criteria for the tender requirement will be chosen with the Analytical Hierarchy Process (AHP) which finally would be evaluated to determine the tender winner. AHP should help to elaborate the problem into multiple complex criteria, forming a hierarchy. The AHP implementation requires primary data from questionnaire and secondary data from existing research and policies. AHP calculation process is then used to process the data in the form of scores from the distributed questionnaire. The result of the AHP calculation was used to evaluate each offer from the goods and services providers, while finally done using the method of knockout by passing grade. The dominant factors that influenced the final decision making includes financial power (30.79%), Materials and equipments (8.55%), health and safety (4.59%), technical competence (8.91%), and experience (2.9%). AHP was proven to be very effective when utilized to evaluate e-tendering offer documents
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