Implementation of Modified Backpropagation with Conjugate Gradient as Microarray Data Classifier with Binary Particle Swarm Optimization as Feature Selection for Cancer Detection
Cancer is one of the deadliest diseases in the world that needs to be handled as early as possible. One of the methods to detect the presence of cancer cells early on is by using microarray data. Microarray data can store human gene expression and use it to classify cancer cells. But one of the chal...
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| Format: | Article |
| Language: | English |
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LPPM ISB Atma Luhur
2020-09-01
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| Series: | Jurnal Sisfokom |
| Subjects: | |
| Online Access: | http://jurnal.atmaluhur.ac.id/index.php/sisfokom/article/view/978 |
| _version_ | 1797284455301251072 |
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| author | Muhammad Naufal Mukhbit Amrullah Adiwijaya Adiwijaya Widi Astuti |
| author_facet | Muhammad Naufal Mukhbit Amrullah Adiwijaya Adiwijaya Widi Astuti |
| author_sort | Muhammad Naufal Mukhbit Amrullah |
| collection | DOAJ |
| description | Cancer is one of the deadliest diseases in the world that needs to be handled as early as possible. One of the methods to detect the presence of cancer cells early on is by using microarray data. Microarray data can store human gene expression and use it to classify cancer cells. But one of the challenges of using microarray is its vast number of features, not proportional to its small number of samples. To resolve that problem, dimensionality reduction is needed to reduce the number of features stored in microarray data. Binary Particle Swarm Optimization (BPSO) is one of the methods to reduce dimensionality of microarray data that can increase classification performance. Although when combined with Backpropagation, BPSO still shows a relatively low performance. In this research, Modified Backpropagation with Conjugate Gradient is used to classify data that has been reduced with BPSO. The average accuracy result of BPSO+CGBP is 86.1%, giving it an improvement compared to BPSO+BP which averaged to 80.8%. |
| first_indexed | 2024-03-07T17:49:15Z |
| format | Article |
| id | doaj.art-d575d1a154d240f5a885ec85894d7c10 |
| institution | Directory Open Access Journal |
| issn | 2301-7988 2581-0588 |
| language | English |
| last_indexed | 2024-03-07T17:49:15Z |
| publishDate | 2020-09-01 |
| publisher | LPPM ISB Atma Luhur |
| record_format | Article |
| series | Jurnal Sisfokom |
| spelling | doaj.art-d575d1a154d240f5a885ec85894d7c102024-03-02T14:30:18ZengLPPM ISB Atma LuhurJurnal Sisfokom2301-79882581-05882020-09-019333934910.32736/sisfokom.v9i3.978569Implementation of Modified Backpropagation with Conjugate Gradient as Microarray Data Classifier with Binary Particle Swarm Optimization as Feature Selection for Cancer DetectionMuhammad Naufal Mukhbit Amrullah0Adiwijaya Adiwijaya1Widi Astuti2Telkom UniversityTelkom UniversityTelkom UniversityCancer is one of the deadliest diseases in the world that needs to be handled as early as possible. One of the methods to detect the presence of cancer cells early on is by using microarray data. Microarray data can store human gene expression and use it to classify cancer cells. But one of the challenges of using microarray is its vast number of features, not proportional to its small number of samples. To resolve that problem, dimensionality reduction is needed to reduce the number of features stored in microarray data. Binary Particle Swarm Optimization (BPSO) is one of the methods to reduce dimensionality of microarray data that can increase classification performance. Although when combined with Backpropagation, BPSO still shows a relatively low performance. In this research, Modified Backpropagation with Conjugate Gradient is used to classify data that has been reduced with BPSO. The average accuracy result of BPSO+CGBP is 86.1%, giving it an improvement compared to BPSO+BP which averaged to 80.8%.http://jurnal.atmaluhur.ac.id/index.php/sisfokom/article/view/978microarraydata miningbackpropagationconjugate gradientbinary particle swarm optimizationdata classification |
| spellingShingle | Muhammad Naufal Mukhbit Amrullah Adiwijaya Adiwijaya Widi Astuti Implementation of Modified Backpropagation with Conjugate Gradient as Microarray Data Classifier with Binary Particle Swarm Optimization as Feature Selection for Cancer Detection Jurnal Sisfokom microarray data mining backpropagation conjugate gradient binary particle swarm optimization data classification |
| title | Implementation of Modified Backpropagation with Conjugate Gradient as Microarray Data Classifier with Binary Particle Swarm Optimization as Feature Selection for Cancer Detection |
| title_full | Implementation of Modified Backpropagation with Conjugate Gradient as Microarray Data Classifier with Binary Particle Swarm Optimization as Feature Selection for Cancer Detection |
| title_fullStr | Implementation of Modified Backpropagation with Conjugate Gradient as Microarray Data Classifier with Binary Particle Swarm Optimization as Feature Selection for Cancer Detection |
| title_full_unstemmed | Implementation of Modified Backpropagation with Conjugate Gradient as Microarray Data Classifier with Binary Particle Swarm Optimization as Feature Selection for Cancer Detection |
| title_short | Implementation of Modified Backpropagation with Conjugate Gradient as Microarray Data Classifier with Binary Particle Swarm Optimization as Feature Selection for Cancer Detection |
| title_sort | implementation of modified backpropagation with conjugate gradient as microarray data classifier with binary particle swarm optimization as feature selection for cancer detection |
| topic | microarray data mining backpropagation conjugate gradient binary particle swarm optimization data classification |
| url | http://jurnal.atmaluhur.ac.id/index.php/sisfokom/article/view/978 |
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