Domas, Zico Karya Saputra and Rizkiawan, M and Rakhmadi, Roby (2022) Efforts of Performance Optimization: The Experiment on Ten Accounting Datasets. Efforts of Performance Optimization: The Experiment on Ten Accounting Datasets, 13 (3). pp. 172-184. ISSN 2541-5832
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Abstract
In the big data and digitalizationera, fast-accurate decision-making has become a basic need,so data mining has a crucial role. The decision tree algorithm is quite commonly applied for classification functions,but performance level must always be evaluated for optimizingaccuracy rate. Several optimization methods to accommodate these objectives include GA-bagging, PSO-bagging, forward selection, backward elimination, SMOTE, under-sampling, GA-Adaboost, and ABSMOTE-WIGFS. The results of the decision tree experiment on tentypes of accounting-finance datasets used in this study obtained results with anaverage accuracy of 83.46%, anaverage precision of 65.64%, and anaverage AUCof 71.9%, while the majorityof various optimizationsare proven in improving the performance of decisiontree algorithm where the application of ABSMOTE-WIGFS method is proven in providing the best rate with an average accuracy 87.71%, an average precision 87.09%, and an average AUC 84.87%, so it can be concluded that various optimization efforts are worth to be applied incase of accounting-finance themes for increasing the performance rate.Furthermore, the next research can prove these methods in other fields outsideof accounting cases
| Item Type: | Article |
|---|---|
| Subjects: | H Social Sciences > HA Statistics |
| Divisions: | Fakultas Ilmu Sosial dan Ilmu Politik (FISIP) > Prodi Hubungan Internasional |
| Depositing User: | M.Si. Roby Rakhmadi |
| Date Deposited: | 13 Jan 2023 00:43 |
| Last Modified: | 13 Jan 2023 00:43 |
| URI: | http://repository.lppm.unila.ac.id/id/eprint/47778 |
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