PERBANDINGAN METODE DECISION TREE DENGAN NAÏVE BAYES DALAM KLASIFIKASI TUMOR OTAK CITRA MRI
In medical image classification, Machine Learning algorithm is commonly implemented. Decision Tree and Naive Bayes are commonly used method in medical image classification. Therefore, a comparison between Decision Tree and Naive Bayes algorithm is concluded to get the performance of the classificati...
Saved in:
| Main Author: | |
|---|---|
| Format: | Book |
| Published: |
2020-06-20.
|
| Subjects: | |
| Online Access: | Link Metadata |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
MARC
| LEADER | 00000 am a22000003u 4500 | ||
|---|---|---|---|
| 001 | repoupnvj_6844 | ||
| 042 | |a dc | ||
| 100 | 1 | 0 | |a Suci Dilasari Kamil, . |e author |
| 245 | 0 | 0 | |a PERBANDINGAN METODE DECISION TREE DENGAN NAÏVE BAYES DALAM KLASIFIKASI TUMOR OTAK CITRA MRI |
| 260 | |c 2020-06-20. | ||
| 500 | |a http://repository.upnvj.ac.id/6844/13/ABSTRAK.pdf | ||
| 500 | |a http://repository.upnvj.ac.id/6844/14/AWAL.pdf | ||
| 500 | |a http://repository.upnvj.ac.id/6844/15/BAB%201.pdf | ||
| 500 | |a http://repository.upnvj.ac.id/6844/16/BAB%202.pdf | ||
| 500 | |a http://repository.upnvj.ac.id/6844/17/BAB%203.pdf | ||
| 500 | |a http://repository.upnvj.ac.id/6844/18/BAB%204.pdf | ||
| 500 | |a http://repository.upnvj.ac.id/6844/19/BAB%205.pdf | ||
| 500 | |a http://repository.upnvj.ac.id/6844/20/DAFTAR%20PUSTAKA.pdf | ||
| 500 | |a http://repository.upnvj.ac.id/6844/21/RIWAYAT%20HIDUP.pdf | ||
| 500 | |a http://repository.upnvj.ac.id/6844/22/LAMPIRAN.pdf | ||
| 500 | |a http://repository.upnvj.ac.id/6844/23/ARTIKEL%20KI.pdf | ||
| 520 | |a In medical image classification, Machine Learning algorithm is commonly implemented. Decision Tree and Naive Bayes are commonly used method in medical image classification. Therefore, a comparison between Decision Tree and Naive Bayes algorithm is concluded to get the performance of the classification methods to MRI, with preprocess of grayscale, K- means clustering for segmentation, and GLCM for texture feature extraction. This study will implement texture analysis with contrast, correlation, energy, and homogeneity to classify the images to two class: brain tumor and non-brain tumor. From the study, based on the value of accuracy, specificity, and sensitivity, Decision Tree has higher values compared to Naive Bayes which are 96% accuracy, 96% specificity, and 96% sensitivity compared to Naive Bayes value of 91% accuracy, 90% specificity, and 93% sensitivity. | ||
| 546 | |a id | ||
| 546 | |a id | ||
| 546 | |a id | ||
| 546 | |a id | ||
| 546 | |a id | ||
| 546 | |a id | ||
| 546 | |a id | ||
| 546 | |a id | ||
| 546 | |a id | ||
| 546 | |a id | ||
| 546 | |a id | ||
| 690 | |a T Technology (General) | ||
| 655 | 7 | |a Thesis |2 local | |
| 655 | 7 | |a NonPeerReviewed |2 local | |
| 787 | 0 | |n http://repository.upnvj.ac.id/6844/ | |
| 787 | 0 | |n https://repository.upnvj.ac.id | |
| 856 | 4 | 1 | |u http://repository.upnvj.ac.id/6844/ |z Link Metadata |