ANALISIS FAKTOR PENYEBAB TERJADINYA COST OVERRUN PADA PROYEK PRESERVASI JALAN

Fatchurrohman Fatchurrohman, Muhammad Zaki, Darmawan Pontan, Endah Kurniyaningrum

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The background to this research is that other important things in implementing construction projects, apart from quality and time, are costs. The construction projects studied were road preservation projects carried out by construction service companies from 2015 to 2022. There were eighteen (18) road preservation projects studied throughout Indonesia, both on the islands of Sumatra, Java, Kalimantan, Sulawesi and Papua. During implementation, there was an increase in costs (cost overrun) so that the company's profit target was not met and disrupted the performance of work completion.

The purpose of this research is to determine the causes of the increase in implementation costs relative to the direct costs that have been determined so that repeated failures do not occur in implementing road preservation projects.

This type of research is associative research with a quantitative approach. The variable used is cost overrun as the dependent variable. Meanwhile, the independent variables are estimated costs, materials, labor, equipment, project finances, project documents, implementation time, natural environment, implementation of work relations and economic feasibility as well as local sub-contractors.

The data collection technique in this research used a questionnaire distributed to respondents, namely the project team of road preservation project managers, totaling 54 respondents from 2015 to 2022 at state companies in the construction services sector.

The results of this research are that the factors causing cost overrun in road preservation projects are material variables, equipment variables and local sub-subcontractor variables. The dominant factors causing cost overruns in road preservation projects are first, the material variable with a regression coefficient of 0.554. Second, the local sub-subcontractor variable with a reference coefficient of 0.376. Lastly, the equipment variable has a regression coefficient of 0.271.


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DOI: https://doi.org/10.31869/rtj.v7i2.5476

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