Unit cost modelling of public building project in Kepulauan Riau- Indonesia / Indrastuti

• Main Author: Indrastuti, -
• Format: Thesis
• Published: 2014
• Subjects: T Technology (General); TA Engineering (General). Civil engineering (General)
• Online Access: http://studentsrepo.um.edu.my/8740/4/Indrastuti.pdf; http://studentsrepo.um.edu.my/8740/

This research analyzes the uncertainty of unit cost that influences the cost of the frame element of a building and how to model it using the simulation method for public building projects in Kepulauan Riau Province, Indonesia. The research is expected to be able to provide a great benefit to the stakeholders. Monte Carlo simulation technique is used as a tool in the analysis of the model; it encompasses the traditional building economics principle that a complex building cost-estimating problem should be broken down (analysed) into recognisable parts such as work unit rate, which can be cost, and which can be determined by tornado graph and spiderplots individually and then reassembled to the whole to provide the total estimate of the cost of the frame element of the building. Each of these unit costs of work is represented by a probability density function. The data collected were from the contract documents, which include the index of material usage, index of labour needed and index of tools used by the unit work of reinforcement, concrete, light formwork and heavy formwork. The study shows that the reinforcement unit has the most influence on the frame element, and the materials have the most influence on the reinforcement work. The probability density and cumulative probability functions curves produced as the result of this study allow a cost estimator to know the associated degree of risk of an estimate by interpreting directly from the curves. The estimate can be in total cost or subtotal of element group. The incorporation of time and location factors enable the formulated cost model to be used in cost prediction of price for future government building projects at various locations in Indonesia. A close assessment of the graph indicates that the pdf curves were all positively skewed – a pattern that was consistent with the prediction of the model. A positive skewed curve indicates that the most likely value (relates to the most frequently observed events of the past) falls towards the risky end of the range of likely outcomes.The main reason why the most likely value is inherently optimistic and risky is the fact that individual costs almost always display more scope to overrun than they do opportunity to improve. The typical shape of cumulative probabilistic cost is the S-curve. It means that the chances for a work to be implemented at extremely low rates (optimistic) and high rates (pessimistic) are very unlikely, although it is possible theoretically.