دورية أكاديمية
أعرض في EDS

Prediksi Deteksi Penyakit Kanker Payudara dengan Menggunakan Algoritma Decision Tree

التفاصيل البيبلوغرافية
العنوان: Prediksi Deteksi Penyakit Kanker Payudara dengan Menggunakan Algoritma Decision Tree
المؤلفون: Ayu Dian Fitri Mellina, Suhartono Suhartono, M. Ainul Yaqin
المصدر: JISKA (Jurnal Informatika Sunan Kalijaga), Vol 9, Iss 1 (2024)
بيانات النشر: Universitas Islam Negeri Sunan Kalijaga Yogyakarta, 2024.
سنة النشر: 2024
المجموعة: LCC:Information technology
مصطلحات موضوعية: Breast Cancer, Classification, Prediction, Decision Tree, Machine Learning, Information technology, T58.5-58.64
الوصف: Cancer is a deadly disease that is difficult to cure. Early cancer detection can be done through laboratory tests to identify the cancer type. Breast cancer is a type of cancer with initial symptoms in the form of a lump. Data mining and classification methods, such as decision trees with ID3 and C5.0 algorithms, are used to categorize breast cancer. The dataset used is Breast Cancer Coimbra, which was downloaded from UCI Machine Learning in 2018. ID3 has limitations in handling unstructured data and continuous attributes, while C5.0 is better. Both algorithms produce tree models with different levels of accuracy. This study shows that the C5.0 algorithm has the best classification results with 80% accuracy, 84.2% precision, 80% recall, and 80% F1 score. 80% accuracy shows the system's classification ability, so the C5.0 model can be used to predict breast cancer.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
Indonesian
تدمد: 2527-5836
2528-0074
Relation: https://ejournal.uin-suka.ac.id/saintek/JISKA/article/view/4079; https://doaj.org/toc/2527-5836; https://doaj.org/toc/2528-0074
URL الوصول: https://doaj.org/article/b0a250e740ed4465ab403c26a931c602
رقم الأكسشن: edsdoj.b0a250e740ed4465ab403c26a931c602
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:25275836
25280074