Software cost estimation (SCE) can be substantial challenges in software development as it could yield inaccurate results. The SCE failure influences project sustainability which might lead to additional costs and times to complete the project. Previous research has provided empirical evidence that the unsuccessfulness of software cost estimation in public sectors is higher than in private sectors. This is due to the actual cost not in line with the estimation cost. The objective of this paper

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... s to determine the SCE practices in the regional government of Indonesia. This research adopts both quantitative and qualitative approaches. The quantitative approach was conducted by distributing questionnaires to government employees who are involved in cost estimation. RASCH model software was used to analyze the data. The qualitative approach involved interviewing personnel in the cost estimation process in regional government. This research involved seven government agencies in West Sumatera Province, Indonesia. The findings of this study show that current practices of SCE in the regional government of Indonesia are not effective although there is a budget ceiling (pagu anggaran) and owner estimate cost (harga perkiraan sendiri). This paper highlights the reasons for inaccurate results of SCE in public sector due to five factors which are: people who have authority to estimate the software cost, time of the estimation, no tool to estimate the software cost, the frequency of changing the scope and requirements of the project, and the number of changes of scope and requirements. However, this research may not include all the factors that influence software cost estimation in government projects yet. There might be other factors that might influence SCE in the public sector. These factors can assist the regional government of Indonesia to effectively and quantitatively analyze the factors that significantly impact software development in Indonesian regional government context. Those factors can be included as parameters in estimating the software cost and also to enhance the software cost estimation process. Thus, it can reduce the risk of the project from overrunning and over budget.