Hyperparameter Optimization of the Perceptron Algorithm for Determining the Feasibility of Research Proposals and Community Service
Higher education in Indonesia includes diploma, bachelor, master, specialist, and doctoral programmes organised by universities. The Institute for Research and Community Service (LPPM) is in charge of assessing lecturers' proposals. This research aims to optimise the Perceptron algorithm to ass...
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| Format: | Article |
| Language: | Indonesian |
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Universitas Lancang Kuning
2024-11-01
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| Series: | Digital Zone: Jurnal Teknologi Informasi dan Komunikasi |
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| Online Access: | https://journal.unilak.ac.id/index.php/dz/article/view/17812 |
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| author | Lisnawita Lisnawita Guntoro Guntoro Loneli Costaner |
| author_facet | Lisnawita Lisnawita Guntoro Guntoro Loneli Costaner |
| author_sort | Lisnawita Lisnawita |
| collection | DOAJ |
| description | Higher education in Indonesia includes diploma, bachelor, master, specialist, and doctoral programmes organised by universities. The Institute for Research and Community Service (LPPM) is in charge of assessing lecturers' proposals. This research aims to optimise the Perceptron algorithm to assess proposal eligibility using Turnitin plagiarism scores and reviewer scores. The optimisation results show that Perceptron accuracy reaches 99.44% to 99.63% at various training data ratios. GridSearchCV achieved 100% accuracy, while RandomisedSearchCV recorded accuracy between 98.89% to 99.63%. GridSearchCV also had the lowest MSE , despite higher Loss values, indicating a sacrifice in generalisation ability. Perceptron Default and RandomisedSearchCV had higher MSE and Loss, but remained low. GridSearchCV's AUC reached 100%, while Perceptron Default and RandomisedSearchCV showed very high AUC, ranging from 99.25% to 99.98%. Overall, the Perceptron algorithm is effective in assessing proposal eligibility with high accuracy. |
| format | Article |
| id | doaj-art-4a5eb4675e7c4641b3d4d878b3df374b |
| institution | Kabale University |
| issn | 2086-4884 2477-3255 |
| language | Indonesian |
| publishDate | 2024-11-01 |
| publisher | Universitas Lancang Kuning |
| record_format | Article |
| series | Digital Zone: Jurnal Teknologi Informasi dan Komunikasi |
| spelling | doaj-art-4a5eb4675e7c4641b3d4d878b3df374b2024-12-13T09:47:30ZindUniversitas Lancang KuningDigital Zone: Jurnal Teknologi Informasi dan Komunikasi2086-48842477-32552024-11-0115217218110.31849/digitalzone.v15i2.1781217812Hyperparameter Optimization of the Perceptron Algorithm for Determining the Feasibility of Research Proposals and Community ServiceLisnawita Lisnawita0Guntoro Guntoro1Loneli Costaner2Universitas Lancang KuningUniversitas Lancang KuningUniversitas Lancang KuningHigher education in Indonesia includes diploma, bachelor, master, specialist, and doctoral programmes organised by universities. The Institute for Research and Community Service (LPPM) is in charge of assessing lecturers' proposals. This research aims to optimise the Perceptron algorithm to assess proposal eligibility using Turnitin plagiarism scores and reviewer scores. The optimisation results show that Perceptron accuracy reaches 99.44% to 99.63% at various training data ratios. GridSearchCV achieved 100% accuracy, while RandomisedSearchCV recorded accuracy between 98.89% to 99.63%. GridSearchCV also had the lowest MSE , despite higher Loss values, indicating a sacrifice in generalisation ability. Perceptron Default and RandomisedSearchCV had higher MSE and Loss, but remained low. GridSearchCV's AUC reached 100%, while Perceptron Default and RandomisedSearchCV showed very high AUC, ranging from 99.25% to 99.98%. Overall, the Perceptron algorithm is effective in assessing proposal eligibility with high accuracy.https://journal.unilak.ac.id/index.php/dz/article/view/17812researchcommunity serviceperceptronlppmgridsearchcvrandomisedsearchcv |
| spellingShingle | Lisnawita Lisnawita Guntoro Guntoro Loneli Costaner Hyperparameter Optimization of the Perceptron Algorithm for Determining the Feasibility of Research Proposals and Community Service Digital Zone: Jurnal Teknologi Informasi dan Komunikasi research community service perceptron lppm gridsearchcv randomisedsearchcv |
| title | Hyperparameter Optimization of the Perceptron Algorithm for Determining the Feasibility of Research Proposals and Community Service |
| title_full | Hyperparameter Optimization of the Perceptron Algorithm for Determining the Feasibility of Research Proposals and Community Service |
| title_fullStr | Hyperparameter Optimization of the Perceptron Algorithm for Determining the Feasibility of Research Proposals and Community Service |
| title_full_unstemmed | Hyperparameter Optimization of the Perceptron Algorithm for Determining the Feasibility of Research Proposals and Community Service |
| title_short | Hyperparameter Optimization of the Perceptron Algorithm for Determining the Feasibility of Research Proposals and Community Service |
| title_sort | hyperparameter optimization of the perceptron algorithm for determining the feasibility of research proposals and community service |
| topic | research community service perceptron lppm gridsearchcv randomisedsearchcv |
| url | https://journal.unilak.ac.id/index.php/dz/article/view/17812 |
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