TOTAL DISRUPTION OF PERFORMANCE FOR SOFTWARE PROGRAMMER TEAM SELECTION

  • Fitria Fitria (1*) Institut Teknologi dan Bisnis Bank Rakyat Indonesia
  • Neneng Rachmalia Feta (2) BRI Institute of Technology and Business

  • (*) Corresponding Author
Keywords: Total Disruption Of Performance, Interdependence, Team Selection, Skill

Abstract

The lack of skills of the development team is one factor the failure of software development project team. Interdependency based selection that is considered can increase the chances of team success does not consider skills in the calculation of total disruption of performance. Improvement total disruption of performance formula by adding skill variables can reduce the risk of project failure, in terms of the number of requirements that are delays and bugs/ errors

Downloads

Download data is not yet available.

References

M. Woźniak, “Sustainable approach in it project management—methodology choice vs. Client satisfaction,” Sustain., vol. 13, no. 3, pp. 1–21, 2021, DOI: 10.3390/su13031466.

T. F. Kusumasari, “Instruments Measurement Design of Human Behavior in Collaborative Software Construction.”

P. Holtkamp, Competency Requirements of Global Software Development Philipp Holtkamp Competency Requirements of Global Software Development. 2015.

S.-C. Hsu, K.-W. Weng, Q. Cui, and W. Rand, “Understanding the complexity of project team member selection through agent-based modeling,” Int. J. Proj. Manag., vol. 34, pp. 82–93, Jan. 2016, doi: 10.1016/j.ijproman.2015.10.001.

W. P. Millhiser, C. A. Coen, and D. Solow, “Understanding the role of worker interdependence in team selection,” Organ. Sci., vol. 22, no. 3, pp. 772–787, 2011, DOI: 10.1287/orsc.1100.0549.

Fitria and I. G. B. B. Nugraha, Formation of Software Programmer Team Based on Skill Interdependency. 2018.

A. R. Gilal, M. Omar, J. Jaafar, K. I. M. Sharif, A. W. Mahessar, and S. Bin Basri, “Software development team composition: Personality types of programmer and complex network,” 2017.

D. Karaboga and B. Akay, “A comparative study of Artificial Bee Colony algorithm,” Appl. Math. Comput., vol. 214, no. 1, pp. 108–132, 2009, DOI: https://doi.org/10.1016/j.amc.2009.03.090.

J. Lyle M. Spencer and S. M. Spencer, Competence at Work: Models for Superior Performance. Japan Productivity Center. Wiley, 1993.

E. S. Mtsweni, T. Hörne, and J. A. van der Poll, “Soft Skills for Software Project Team Members,” Int. J. Comput. Theory Eng., vol. 8, no. 2, pp. 150–155, 2016, DOI: 10.7763/ijcte.2016.v8.1035.

A. R. Gilal, J. Jaafar, S. Basri, M. Omar, and A. Abro, “Impact of software team composition methodology on the personality preferences of Malaysian students,” in 2016 3rd International Conference on Computer and Information Sciences (ICCOINS), 2016, pp. 454–458, doi: 10.1109/ICCOINS.2016.7783258.

ISACA, The Risk IT Framework. ISACA, 2009.

B. C. D. Anda, D. I. K. Sjøberg, and A. Mockus, “Variability and reproducibility in software engineering: A study of four companies that developed the same system,” IEEE Trans. Softw. Eng., vol. 35, no. 3, pp. 407–429, 2009, DOI: 10.1109/TSE.2008.89.

D. T. Roberts, “Applying risk assessment at the worker level,” in 2017 Petroleum and Chemical Industry Technical Conference (PCIC), 2017, pp. 381–386, DOI: 10.1109/PCICON.2017.8188758.

M. T. Riaz, M. S. Jahan, K. S. Arif, and W. H. Butt, “Risk Assessment on Software Development using Fishbone Analysis,” in 2019 International Conference on Data and Software Engineering (ICoDSE), 2019, pp. 1–6, DOI: 10.1109/ICoDSE48700.2019.9092727.

Published
2022-02-18
How to Cite
[1]
F. Fitria and N. Feta, “TOTAL DISRUPTION OF PERFORMANCE FOR SOFTWARE PROGRAMMER TEAM SELECTION”, jitk, vol. 7, no. 2, pp. 53-60, Feb. 2022.
Article Metrics

Abstract viewed = 112 times
PDF downloaded = 79 times