Validated Software Cost Estimation Factors for Government Projects using Rasch Measurement Model

Rianti Rozalina (1), Zulkefli Mansor (2)
(1) Universiti Kebangsaan Malaysia
(2) Universiti Kebangsaan Malaysia
Fulltext View | Download
How to cite (IJASEIT) :
Rozalina, Rianti, and Zulkefli Mansor. “Validated Software Cost Estimation Factors for Government Projects Using Rasch Measurement Model”. International Journal on Advanced Science, Engineering and Information Technology, vol. 8, no. 5, Oct. 2018, pp. 1890-6, doi:10.18517/ijaseit.8.5.6386.
Software cost estimation (SCE) in software management can be a complicated task, as it could yield inaccurate results. Based on new empirical evidence, Public sectors more often face estimation failure, which causes projects to over shoot budgets, get delayed, face termination or the project scope or requirement to remain incomplete. Hence, the main aim of this paper is to identify the critical factors that significantly impact SCE in the context of software development in the Indonesian regional government. This research employs a quantitative approach, in which a questionnaire is used as the data collection instrument. The data is analysed using a RASCH model. This study is conducted in the regional government of West Sumatera Province, Indonesia. The result of the study reveals that there are six critical factors that significantly impact SCE results in a government project. These critical factors are programmer capability, top management support, the understanding of top management regarding the objectives of the project, risk management, knowledge, competency of the project manager, and top management involvement in the project.

Ramesh, M. R. R., & Reddy, C. S. (2016) “Difficulties in software cost estimation: A survey,” International Journal of Scientific Engineering and Technology, 5(5), 10-13.

Shekhar, S. & Kumar, U. (2016) “Review of various software cost estimation techniques,” International Journal of Computer Applications, 141(11), 31-34.

Leena, N. (2012) “Software cost estimation -A case study. Asian,” Journal of Computer Science and Information Technology, 10, 283-285.

Ubani, E. C., et al. (2015) Analysis of factors responsible for project cost underestimation in Nigeria, III (2), 1-12.

Haslindah Sutan Ahmad Nawi, Azizah Abd.Rahman & Othman Ibrahim. (2014) “Government ICT project failure factors: Project stakeholders’ views,” Journal of Information Systems Research and Innovation. 69-77. Available: http://seminar.utmspace.edu.my/jisri/.

Mansor, Z. et al. (2016) “Ruler for effective cost management practices in Agile software development projects,” Advanced Science Letters, 22, 1977-1980

Chaos Report. (2014). The Standish Group Report. Project Smart.

Imam, K. & Arry, A A. (2015) “Development of analogy-based estimation method for software development cost estimation in government agencies,” International Conference on Electrical Engineering and Informatics (ICEEI) 2017, (90).

Sholiq, et al. (2016) “A model to determine cost estimation for software development projects of small and medium scales using case points,” Journal of Theoretical and Applied Information Technology. 85(1).

Medvedska, O., & Berzisa, S. (2015) Selection of SoftwareDevelopment Project Lifecycle Model in Government Institution, 5-11. Available: http://doi.org/10.1515/itms-2015-0001

Rajkumar, G. & Alagarsamy, K. (2013) “The most common success factors in cost estimation,” International Journal Computer Technology & Application 4(1), 58-61

Potdar et al. (2014) “Factors influencing on cost estimation for software development,” Global Journal of Advanced Engineering Technologies, 3(2), 119-123. Available: http://www.gjaet.com/wpcontent/uploads/2014/05/factorsinfluencingoncostestimation-for-softwaredevelopment2.pdf

Sommerville, I. (2011) Software Engineering. Horton. M. 9th. The United States. Pearson.

Mansor, Z. et al. (2016) “Issues and challenges of cost management in agile software development projects,” Advanced Science Letters. Available: http://doi.org/10.1166/asl.2016.7752

GAO.(2009). Best practices for developing and managing capital program costs. GAO Cost Estimating and Assessment Guide. The United States.

Mansor, Z. et al. (2015) “Success factors of cost management in

agile software development projects,” in PROC of ICONI 2015 Symposium.

Phongpaibul, M. & Aroonvatanaporn, P. (2014) Standardized Cost Estimation in Thai Government’ s Software Development Projects.

Singh, K. & Dwivedi, U. (2014) “A survey various cost & effort estimation models,” International Journal of Advanced Research in Computer Science and Software Engineering, 8(4), 1113-1116.

Renny, S. D. et al. (2015). Use Case Point - Activity-Based Costing: Metode Baru Untuk Mengestimasi Biaya Pengembangan Perangkat Lunak. (5), 318-323.

Boehm, B. W. (2017). Software Cost Estimation Meets Software Diversity. Proceedings - 2017 IEEE/ACM 39th International Conference on Software Engineering Companion, ICSE-C 2017. (495-496).

Boone, W. J. (2016). “Rasch Analysis for Instrument Development: Why, When, and How?,” CBE Life Science Education, 15 (4).

Engelhar, G. & Stefanie, A.W. (2013). Rating Quality Studies Using Rasch Measurement Theory. Research Report 2013-3. College Board.

Bambang, S. & Wahyu, W. (2014) Aplikasi Model Rasch Untuk Penelitian Ilmu-Ilmu Sosial. Cimahi.Trim Komunikata Publishing House.

Linacre, J. M. (2012) A user’s guide to Winsteps: Rasch Model Computer Programs. Chicago: MESA Press

Authors who publish with this journal agree to the following terms:

    1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
    2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
    3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).