Isnani, Yuni (2021) Klasifikasi Penyakit Kanker Kulit Menggunakan Metode K- Nearest Neighbor. Tugas Akhir thesis, University of Technology Yogyakarta.
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Abstract
ABSTRACT Skin cancer is an abnormal and uncontrolled growth of skin cells. Skin cancer is a type of cancer that is often found in America. According to the American Academy of Dermatology, it is estimated that nearly 9,500 Americans are diagnosed with skin cancer every day. The cause of skin cancer is a DNA mutation that causes abnormal growth of certain cells in the skin. This DNA mutation in skin tissue is triggered by exposure to ultraviolet light. This ultraviolet light can cause damage to cells in the skin, causing skin cancer. Data Mining is a series of processes to explore the added value of a large data set in the form of knowledge that has not been known manually. K-Nearest Neighbor is the simplest method, easy to implement by only setting one parameter k. But K-Nearest Neighbor also has several major weaknesses. To overcome these shortcomings, you can do one way, namely making improvements with class probability estimates. This study classifies skin cancer using the K-Nearest Neighbor method. Based on the test results with the number of training data 90 and 45 test data taken randomly, the results of the accuracy rate using the K-Nearest Neighbor method are 45%. Keywords: K-Nearest Neighbor, Skin Cancer, Classification
| Item Type: | Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir) |
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| Subjects: | T Technology > T Technology (General) |
| Divisions: | Fakultas Sains Dan Teknologi > S1 Informatika |
| Depositing User: | Kaprodi S1 Informatika UTY |
| Date Deposited: | 27 Mar 2021 03:56 |
| Last Modified: | 27 Mar 2021 03:56 |
| URI: | http://eprints.uty.ac.id/id/eprint/7216 |
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