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A Decision Tree Model for Software Development Teams
Abdul Rehman Gilal1, Mazni Omar2, Ruqaya Gilal3, Ahmed Waqas4, Sharjeel Afridi5, Jafreezal Jaafar6

1Abdul Rehman Gilal, Sukkur IBA University, Pakistan.

2Mazni Omar, University Utara Malaysia.

3Ruqaya Gilal, University Utara Malaysia.

4Ahmed Waqas, Sukkur IBA University, Pakistan.

5Sharjeel Afridi, Sukkur IBA University, Pakistan.

6Jafreezal Jaafar, University Technology Petronas, Malaysia.

Manuscript received on 03 February 2019 | Revised Manuscript received on 10 February 2019 | Manuscript Published on 22 March 2019 | PP: 241-245 | Volume-8 Issue-5S April 2019 | Retrieval Number: ES3422018319/19©BEIESP

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Different theoretical personality models for team composition proved to be inconsistent, posing validity challenges and missing guidance for personnel selection in software development. Due to these impacting issues, this study has produced a decision tree model for software team composition for effective team performance. The model is based on personality types (i.e., collected using Myer Briggs Type Indicator (MBTI)), gender and team role (i.e., only team leader and programmer) to predict team performance (i.e., effective or ineffective). Experimental data, collected from software engineering students of Universiti Teknologi Petronas (UTP) Malaysia, was used to develop and validate the model. In order to develop and validate the model, C4.5 algorithm and 10-fold cross validation methods were used respectively. The results indicate that Judging Perceiving (JP) personality pair isone of the significant attributes to identify the team performance. At the end, the model was observed acceptable during validation process by obtaining satisfactory prediction accuracy 70.48%.

Keywords: Team Composition; Decision Tree; Personality; MBTI.
Scope of the Article: Recent Trends & Developments in Computer Networks