Application of Bayesian Regularization Algorithm for Evaluation of Performance Software Complexity Prediction Model Based On Requirement
Wartika1, Ford Lumban Gaol2, Ariadi Nugroho3, Bahtiar Shaleh Abbas4
1Wartika, Program Doctor Of Computer Science, Binus Graduate Program, Binus University.
2Ford Lumban Gaol , Reseacher In The Field Of Computer Science, Lecturer At Program Doctor Of Computer Science, Binus University.
3Ariadi Nugroho, Practitioners In The Field Of Information Technology, Work At BTPN Bank, Reseacher In The Field Of Computer Science.
4Bahtiar Saleh Abbas, Reseacher In The Field Of Computer Science, Lecturer At Program Doctor Of Computer Science, Binus University.
Manuscript received on 7 August 2019. | Revised Manuscript received on 14 August 2019. | Manuscript published on 30 September 2019. | PP: 2530-2535 | Volume-8 Issue-3 September 2019 | Retrieval Number: C4715098319/2019©BEIESP | DOI: 10.35940/ijrte.C4715.098319
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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: Model performance evaluation is a method and process of evaluating the model that has been built. The model that will be evaluated is software complexity prediction model based on requirement. This model allows measuring software complexity before actual design and implementation. The experiment used three datasets namely training dataset, validation data set , and test dataset. For performance evaluation using Mean squared error. Mean squared error is very good at giving a description of how consistent the model is built. By minimizing the value of mean squared error, it means minimizing model variants. Models that have small variants are able to give relatively more consistent results for all input data compared to models with large variants. This research proposes the application of the Bayesian regularization algorithm for evaluating the performance of software complexity prediction model based on requirement. With this research it is expected to know how much the performance of the model that has been built.
Keywords: Algorithm, Prediction, Software, Complexity
Scope of the Article: Regression and Prediction