APLIKASI DIAGNOSIS PENYAKIT KANKER PAYUDARA MENGGUNAKAN ALGORITME C4.5

Prasetia, Agung (2018) APLIKASI DIAGNOSIS PENYAKIT KANKER PAYUDARA MENGGUNAKAN ALGORITME C4.5. Other thesis, STMIK Amikom Purwokerto.

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Abstract

Cancer is the growth of abnormal new cells that grow beyond normal limits, and can then attack the part next to the body and spread to other organs. Breast cancer is a serious health problem either in Indonesia or in the world. Breast cancer is the second most common cancer in the world and is the most frequent cancer among women with an estimated 1.67 million new cancer cases diagnosed. In Indonesia the disease of breast cancer is the cancer with the highest prevalence in Indonesia amounted to 61,682 sufferers. According to the data on the hospital of Dadi Keluarga breast cancer patients experience increased from the year 2015 to 2017, i.e., to 11,443 patients in 2017. The high cases of the disease in Indonesia requires that sufferers of breast cancer to do the inspection rate of malignancy of breast cancer with breast cancer stage types. In sufferers of breast cancer that is already in the stage of treatment, intensive examination shall be carried out, the detection rate of malignancy of breast cancer on a regular basis is very important. In general, the level of detection of the malignancy of breast cancer is by way of the prognosis. The prognosis is "best guesses" medical team in determining the RID or whether a patient of breast cancer. In addition, with the prognosis, the other way is the utilization of bio informatic by using data mining techniques. This research aims to classify the degree of malignancy of breast cancer using techniques of data mining algorithms C4.5 with the datasets that are used i.e. Dataset Wisconsin Breast Cancer. The results of modeling with algorithm C4.5 obtained accuracy of 96,047% and generate rules to apply to android application that can be used to classify the degree of malignancy of breast cancer. Based on the results of the test with Black Box testing testing and User Acceptance Test (UAT). Thus, it can be concluded that the application rate of diagnosis of malignancy of breast cancer using an algorithm C4.5 can be helpful for classifying breast cancer.

Item Type: Thesis (Other)
Additional Information: Dosen Pembimbing: Kuat Indartono, ST., M.Eng
Uncontrolled Keywords: Data Mining, Breast Cancer, C4.5 Algorithm.
Subjects: R Medicine > R Medicine (General)
T Technology > T Technology (General)
Divisions: Fakultas Ilmu Komputer > Informatika
Depositing User: UPT Perpustakaan Pusat Universitas Amikom Purwokerto
Date Deposited: 14 Apr 2021 05:24
Last Modified: 14 Apr 2021 05:24
URI: http://eprints.amikompurwokerto.ac.id/id/eprint/897

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